WANG Jiangkun
をテンプレートにして作成
[
トップ
] [
新規
|
一覧
|
単語検索
|
最終更新
|
ヘルプ
|
ログイン
]
開始行:
[[AIRBiS project>https://adaptive.u-aizu.ac.jp/aslint/index.php?AIRBiS%20Project]]
----
CENTER:COLOR(#81111F){SIZE(60){''AIRBiS Project''}}
CENTER:COLOR(#81111F){SIZE(30){''AI-Powered Hardware-Software Platform Co-design for Pneumonia Detection [肺炎検出のための AI 主導のハードウェアとソフトウェアのプラットフォームの協調設計]''}}
----
Project: [[Cyber-physical AI-Powered Platform for Pneumonia Detection>http://web-ext.u-aizu.ac.jp/misc/benablab/airbis.html]]
Refer: [[D-RPS & D-RPR スケジュール>https://docs.google.com/document/d/1-4Rwm3yFtae1YHwawW5hJN11A5C6CaBTY-GyEq5dKL0/edit]], [[Z.Wang>https://adaptive.u-aizu.ac.jp/aslint/index.php?Zhishang%20Wang]]
*COLOR(gold){Doctoral Dissertation} [#zf912297]
//*Doctoral Dissertation [#f5568590]
-COLOR(#81111F){SIZE(20){Dissertation Title}}
--COLOR(#81111F){SIZE(20){(English): Scaling Pneumonia Detection Inference Based on Reconfigurable AI-Enabled System}}
--COLOR(#81111F){SIZE(20){(Japanese): AI に基づいた再構成可能なシステムによるスケーリング可能な肺炎検出推論}}
*COLOR(gold){Doctoral Dissertation Review Procedure} ([[AY2023 Autumn Ref>https://www.u-aizu.ac.jp/en/graduate/curriculum/doctor/]]) [#cf0b2887]
|Date|Task|
|☑️Nov 4, 2022|Submission of dissertation title and list of referees.|
|☑️March 4, 2023|Finish 1st draft of the Doctoral Dissertation.|
|☑️March 1~10, 2023|Send schedule request to referees (Professors).|
|☑️March 31, 2023|Submission of the documents for the Doctoral Dissertation Preliminary Review.|
|☑️April 14, 2023|Doctoral dissertation Preliminary Review.|
|☑️April 21, 2023|Submission of the documents for the Doctoral Dissertation Preliminary Review Result.|
|☑️May 31, 2023|Submission of the documents for the Doctoral Dissertation final Review.|
|☑️June 13, 2023|Doctoral Dissertation Final Review.|
|☑️June 26, 2023|Submission of the final review report|
|☑️Aug 2, 2023|Submission of the materials for the presentation.|
|☑️Aug 9, 2023|Dissertation presentation date.|
|Aug 15, 2023|Submission of finalized Dissertations and their abstracts.|
|Aug 15, 2023|Submission of the Abstracts of the Results Regarding the Final Doctoral Dissertation Review.|
|Aug 15, 2023|Submission of Confirmation of Online Publication (Repository Listing) of Dissertation Form.|
|Aug 15, 2023|Submission of the Application Form for the Academic Degree.|
//|COLOR(red){Official Due date: Aug 2, 2023}|Submission of the materials for the presentation|
//|COLOR(red){Official Due date: Feb 14, 2023}|Submission of finalized Dissertations and their abstracts|
//|COLOR(red){Official Due date: Feb 14, 2023}|Submission of the Abstracts of the Results Regarding the Final Doctoral Dissertation Review|
//|COLOR(red){Official Due date: Feb 14, 2023}|Submission of Consent to Use of Academic Paper / Repository Registration Request Form|
//|COLOR(red){Official Due date: Feb 14, 2023}|Submission of the Application Form for the Academic Degree|
//|COLOR(red){Official Due date: Feb 17, 2023}|Dissertation presentation|
*AIRBiS progress meeting [#f5568590]
-[[AIRBiS Minutes]]
----
*Background and Motivation [#w522f8b9]
Artificial Intelligence (AI) has recently become a topic of study in different applications including healthcare, in which timely detection of anomalies can play a vital role in patient’s health monitoring. The COVID-19 disease, caused by the SARS-CoV-2 virus, colloquially known as the Corona virus, is disrupting large parts of the world. The standard way to test for COVID-19 is Reverse Transcription Polymerase Chain Reaction (RT-PCR) which uses collected samples from patients. The sensitivity of this test ranges from 60% to 97%. Another method is to analyze the X-ray image of the patents’ lung, which has the accuracy in range 80-90%. The number of patients has exponentially increased during the epidemic, which leads to inefficient diagnosis procedure since it requires doctors to manually diagnosis one by one. The management is also inefficient due to uncoordinated system and lack of quick response and report. Moreover, privacy is an important requirement for the patients’ information and treatment. Delay in patient’s isolations and treatment are associated with number of patients and mortality.
*Research Goal [#df6c5e40]
I will research about a software-hardware Co-design of AI-Enabled Real-time Bio-system.
The research includes the following:
- A deep-learning medical imaging method that could extract COVID-19’s graphical features in order to provide a clinical diagnosis ahead of the pathogenic test, thus saving critical time for disease control. This method will improve the diagnosis efficiency and lift some of the heavy weight of the physicians’ shoulders. The system can identify infected individuals with fast/accurate detection, diagnosis and reporting mechanisms, which is significant helpful to control the outbreak spread of COVID-19 virus.
-A collaborative learning model to preserve the privacy of users’ biomedical data.
-A SW&HW-based smart management platform by combining the advantages of software and hardware (i.e., AI-Chip) in efficient management, high-speed computation and low power consumption. Especially, by a coordinated management, our platform will effectively assist the government to make reasonable strategy, build fast response mechanism for emergency events, and optimize resource allocation.
*Research Schedule [#md706e02]
|Date|Task|
|☑️Aug 1st - Oct 31, 2020| Running demos and study of SW/HW tools in ASL Guidance. |
|☑️Nov 1st - Nov 15, 2020| Prepare paper for "Biomedical Circuits and Systems". |
|☑️Nov 16 - Nov 23, 2020| Check the CNN program from Okada, run on ZCU102 FPGA board and record result. |
|☑️Nov 23 - Nov 30, 2020| Survey current reference papers, update paper for "Biomedical Circuits and Systems". |
|☑️Dec 1st - Dec 4, 2020| Prepare airbis team report and preliminary results in paper. |
|☑️Dec 4 - Dec 11, 2020| Revise and submit papers for ETLTC2021. |
|☑️Dec 12 - Dec 25, 2020| Finish UI-FPGA-Communication function separately. |
|☑️Dec 18 - Dec 29, 2020| Get preliminary results of the AIRBiS system. |
|☑️Jan 1st - Jan 15, 2021| Read paper of "parallel CNN" and prepare slide for RPR1. |
|☑️Jan 16 - Jan 24, 2021| Integrate the AIRBiS system program and get evaluation results. |
|☑️Jan 24 - Jan 29, 2021| Summary the research of AIRBIS system and prepare slide for the RPS4. |
|☑️Feb 1 - Feb 10, 2021| Read paper of "parallel CNN" and prepare slide for RPR2. |
|☑️Feb 8 - Feb 19, 2021| Working on the hardware acceleration design evaluation in FPGA with a bigger input size(64*64 -> 128*128) and more complex CNN model. |
|☑️Feb 22 - Feb 26, 2021| Implementing FL experiment of 3 clients. |
|☑️Mar 1 - Mar 6, 2021| Finish the implementation of COVID-19 test instead of anomalies test. |
|☑️Mar 8 - Mar 13, 2021| Summarize the hardware part of AIRBiS and debug CNN code on pc and FPGA together with Fukuchi. |
|☑️Mar 15 - Apr 3, 2021| Work on the experiment of CNN learning on FPGA. |
|☑️Apr 5 - Apr 10, 2021| Extract information from related papers/researches about experiment results comparing. |
|☑️Apr 12, Apr 20, 2021| Explore ROI solution for the AIRBiS project. |
|☑️Apr 21, May 6, 2021| Read related papers/surveys and enrich the content of the AIRBiS project paper. |
|☑️May 7, May 19, 2021| Carry out AIRBiS experiment with the new dataset. |
|☑️May 20 - June 5, 2021| Deal with the accuracy problem of the new dataset. |
|☑️June 7 - June 16, 2021| Summarize the result of hardware and debug with Xilinx sdsoc. |
|☑️June 17 - June 26, 2021| Summarize the result of FPGA inference and CNN. |
|☑️June 27 - July 10, 2021| Update UI and add heatmap function for COVID-19 detection. |
|☑️July 12 - July 21, 2021| Measure the power consumption of related platforms and the time-cost of convolution function in FPGA. |
|☑️July 22 - Aug 5, 2021| Finish the AIRBiS draft paper. |
|☑️Aug 11 - Sept 23, 2021| Improve the journal paper and prepare for the submission. |
|☑️Sept 24, Oct 4, 2021| Finish the new version of the MDPI journal paper. |
|☑️Oct 5, Oct 25, 2021| Improve the journal paper and submit it to MDPI. |
|☑️Sept 1st, Oct 31, 2021| Investigate, select, modify, print, and assemble the prosthetic arm(hand).|
|☑️Nov 1st, Nov 14, 2021| Journal paper improvement.|
|☑️Nov 15, Nov 23, 2021| Paper revise and resubmit.|
|☑️Nov 24, Nov 25, 2021| Research Progress Presentation.|
|☑️Nov 26, Dec 10, 2021| Begin the research of SNN-based federated learning.|
|☑️Dec 6, Dec 20, 2021| Paper revision and submit it to IEEE Access.|
|☑️Dec 15, Jan 7, 2022| Submit one IEEE conference paper.|
|☑️Jan 7, Jan 11, 2022| Solve the problem of ERROR: [SdsCompiler 83-5004] Build failed. |
|☑️Jan 4, Jan 20, 2022| Quantization optimization of the AIRBiS SW (tensorflow). |
|☑️Jan 13, Jan 28, 2022| Improve ETLTC2022 paper and result. |
|☑️Jan 23, Feb 6, 2022| Finish the final manuscript of the IEEE conference paper. |
|☑️Feb 8, Feb 22, 2022| IEEE conference paper presentation slide and video submission. |
|☑️Feb 12, Feb 25, 2022| Tensorflow-lite experiment for AIRBiS SW (ANN). |
|☑️Feb 24, Mar 16, 2022| Quantization optimization experiment of the AIRBiS HW (xilinx). |
|☑️March 17, April 2, 2022| Update figures and content in paper. Modify AIRBiS parallel inference figure. |
|☑️March 29, April 8, 2022| Update the paper and the answer file for MDPI resubmission. |
|☑️April 9, April 18 2022| Improve the draft according to the meeting discussion. |
|☑️April 19, April 27 2022| Inference time result (real-time) diagram and statistic analysis. |
|☑️April 28, May 8 2022| Combine several tables and diagrams to make the paper concise and clear. |
|☑️May 9 , May 17 2022| Finish some new evaluation experiments on SW(GPU), HW(GPU), and FL(10 clients). |
|☑️May 18, May 25 2022| Update diagrams and tables on SW, HW, and FL. |
|☑️May 26, May 30 2022| Update descriptions of the new diagram and evaluation experiment. |
|☑️May 31, June 7 2022| Update abstract and introduction section. Double-check.|
|☑️June 8rd, June 19, 2022| Update the draft and answer file for the re-submission of MDPI paper. |
|☑️June 20rd, June 26, 2022| Survey papers, and update research plan. |
|☑️June 28, July 4, 2022| Experiments about segmented lung x-ray images. |
|☑️July 5, July 16, 2022| MDPI paper major revision. |
|☑️July 18, August 7, 2022| MDPI paper answer and CNN code checking. |
|☑️August 8, August 11, 2022| AIRBiS-SNN survey and plan. |
|☑️August 12, August 25, 2022| AIRBiS-SNN SW experiment and paper writing. |
|☑️August 26, Sept 18, 2022| Compare the AIRBiS-SNN and AIRBiS-ANN |
|☑️Sept 16, Oct 6, 2022| AIRBiS-SNN HW, Conv core, SNPC. |
|☑️Oct 4, Oct 29, 2022| Revise and update the AIRBiS-SNN manuscript. |
|☑️Oct 31, Nov 10, 2022| Double-check and submit the AIRBiS-SNN paper. |
|☑️Nov 11, Nov 27, 2022| Revise and answer the AIRBiS-SNN paper. |
|☑️Nov 28, Dec 13, 2022| Final Proofreading of the AIRBiS-SNN paper Before Publication. |
|☑️Dec 14, Jan 2, 2023| Prepare and submit an IEEE conference paper. |
|☑️Jan 3, Jan 25,2023| Literature survey about knowledge distillation and SNN works. |
|☑️Jan 26, Feb 11, 2023| Finish the outline of doctoral dissertation.|
|☑️Feb 12, Feb 27, 2023| Finish Chapters 1, 2 and 3 of the doctoral dissertation.|
|☑️Feb 28, Mar 15, 2023| Finish Chapters 4, 5 and 6 of the doctoral dissertation.|
|☑️Mar 16, Mar 31, 2023| Complete the first draft of the doctoral dissertation.|
|☑️Apr 1, Apr 14, 2023| Prepare slide and presentation rehearsal of the Doctoral Dissertation Preliminary Presentation.|
|☑️Apr 15, Apr 21, 2023| Submission of the documents for the Doctoral Dissertation Final Review.|
|☑️Apr 22, May 9, 2023| Prepare international conference itinerary and presentation slides and presentation rehearsal.|
|☑️Apr 10, May 17, 2023| Participate in the 2023 International Conference on Electronics Technology (ICET) in Chengdu, China.|
|☑️May 18, May 29, 2023| Submission of the documents for the Doctoral Dissertation Final Review.|
|☑️May 30, June 13, 2023| Prepare slide and presentation rehearsal of the Doctoral Dissertation Final Presentation.|
|June 14, Aug 20, 2023| Doctoral Dissertation and Academic Degree.|
|Aug 21, Sept 25, 2023| Complete experiments and drafts for new journal paper "A client selection based secure pneumonia detection method".|
CENTER:COLOR(green){Schedule last updated on: 8/14/2023}
*Achievements [#g0c8f9db]
***Accepted Journal Papers [#p4f63a6e]
-Spike-Event X-ray Image Classification for 3D-NoC-Based Neuromorphic Pneumonia Detection
--Jiangkun Wang}, Ogbodo Mark Ikechukwu, Khanh N. Dang, and Abderazek Ben Abdallah. ‘Spike-Event X-ray Image Classification for 3D-NoC-Based Neuromorphic Pneumonia Detection’, Electronics, vol. 11, no. 24, p. 4157, 2022. doi: [[10.3390/electronics11244157>https://doi.org/10.3390/electronics11244157]].
--[[Electronics | Free Full-Text | Spike-Event X-ray Image Classification for 3D-NoC-Based Neuromorphic Pneumonia Detection>https://www2.mdpi.com/2079-9292/11/24/4157]]([[latex>https://drive.google.com/drive/folders/1OFu9lqh5MiP1G7jIez-aPHgPE9jamiY6?usp=sharing]],
[[pdf>https://www2.mdpi.com/2079-9292/11/24/4157/pdf?version=1670978268]])
***Accepted Conference Papers [#p4f63a6e]
-Scaling Deep-Learning Pneumonia Detection Inference on a Reconfigurable Self-Contained Hardware Platform
--Jiangkun Wang}, Khanh N. Dang, and Abderazek Ben Abdallah. ‘Scaling Deep-Learning Pneumonia Detection Inference on a Reconfigurable Self-Contained Hardware Platform’. in 2023 IEEE 6th International Conference on Electronics Technology (ICET), Chengdu, China, May 12-15, 2023, Proceedings, 1–6. IEEE, 2023. ([[latex>https://drive.google.com/drive/folders/1OFu9lqh5MiP1G7jIez-aPHgPE9jamiY6?usp=sharing]],
[[pdf>https://www2.mdpi.com/2079-9292/11/24/4157/pdf?version=1670978268]])
-Efficient AI-Enabled Pneumonia Detection in Chest X-ray Images
--Jiangkun Wang, Miyuka Nakamura, and Abderazek Ben Abdallah, ‘Efficient AI-Enabled Pneumonia Detection in Chest X-ray Images’, in 2022 IEEE 4th Global Conference on Life Sciences and Technologies (LifeTech), Osaka, Japan, March 7-9, 2022, Proceedings, pp. 470–474. IEEE, 2022. doi: [[10.1109/LifeTech53646.2022.9754850>https://doi.org/10.1109/LifeTech53646.2022.9754850]]. ([[latex>https://drive.google.com/drive/folders/1OFu9lqh5MiP1G7jIez-aPHgPE9jamiY6?usp=sharing]],
[[pdf>https://www2.mdpi.com/2079-9292/11/24/4157/pdf?version=1670978268]])
----
@article{wang2022spike,
title = {Spike-Event X-ray Image Classification for 3D-{NoC}-Based Neuromorphic Pneumonia Detection},
author = {Jiangkun Wang and Ogbodo Mark Ikechukwu and Khanh N. Dang and Abderazek Ben Abdallah},
journal = {Electronics},
volume = {11},
number = {24},
pages = {4157},
year = {2022},
month = {Dec},
publisher = {MDPI},
doi = {10.3390/electronics11244157},
}
@inproceedings{wang2023scaling,
title={Scaling Deep-Learning Pneumonia Detection Inference on a Reconfigurable Self-Contained Hardware Platform},
author={Wang, Jiangkun and Khanh N. Dang and Abdallah, Abderazek Ben},
booktitle={2023 IEEE 6th International Conference on Electronics Technology (ICET)},
pages={1--6},
year={2023},
address = {Chengdu, China, May 12-15},
organization={IEEE},
}
@inproceedings{wang2022efficient,
title={Efficient AI-Enabled pneumonia detection in chest x-ray images},
author={Wang, Jiangkun and Nakamura, Miyuka and Abdallah, Abderazek Ben},
booktitle={2022 IEEE 4th Global Conference on Life Sciences and Technologies (LifeTech)},
pages={470--474},
year={2022},
organization={IEEE},
doi = {10.1109/LifeTech53646.2022.9754850},
}
----
*references [#g0821b75]
-[[My Shared GoogleDrive >https://drive.google.com/drive/folders/1B8UHQjNQdfgeHXoB5uskzoVuxlDfwk_q?usp=sharing]]
-[[Ebooks>https://adaptive.u-aizu.ac.jp/aslint/index.php?Free%20Books]]
-[[oki c835 color printer driver for Windows (Please download and run as admin) >https://raw.githubusercontent.com/cdncc/u1/main/uoa/asl/oki_c835_colour_printer_driver/oki_c835_colour_printer_driver.exe]]
-[[Power Estimation with Vivado>https://www.xilinx.com/video/hardware/power-estimation-analysis-using-vivado.html]]
*Updates [#ua5fda23]
-09/29/2020 - Page created by B.
-Update "Research Schedule" by jkun.
--10/29/2020
--11/19/2020
--12/18/2020
--1/26/2021
--2/10/2021
--2/17/2021
--2/24/2021
--3/3/2021
--3/24/2021
--4/6/2021
--4/28/2021
--5/24/2021
--5/27/2021
--6/9/2021
--6/23/2021
--7/19/2021
--8/12/2021
--9/7/2021
--9/28/2021
--10/29/2021
--11/24/2021
--12/17/2021
--2/2/2022
--2/21/2022
--3/14/2022
--3/30/2022
--4/28/2022
--5/30/2022
--6/6/2022
--6/27/2022
--7/29/2022
--9/12/2022
--10/12/2022
--10/28/2022
--12/21/2022
--1/29/2023
--3/2/2023
--4/3/2023
--5/7/2023
--5/19/2023
--8/14/2023
終了行:
[[AIRBiS project>https://adaptive.u-aizu.ac.jp/aslint/index.php?AIRBiS%20Project]]
----
CENTER:COLOR(#81111F){SIZE(60){''AIRBiS Project''}}
CENTER:COLOR(#81111F){SIZE(30){''AI-Powered Hardware-Software Platform Co-design for Pneumonia Detection [肺炎検出のための AI 主導のハードウェアとソフトウェアのプラットフォームの協調設計]''}}
----
Project: [[Cyber-physical AI-Powered Platform for Pneumonia Detection>http://web-ext.u-aizu.ac.jp/misc/benablab/airbis.html]]
Refer: [[D-RPS & D-RPR スケジュール>https://docs.google.com/document/d/1-4Rwm3yFtae1YHwawW5hJN11A5C6CaBTY-GyEq5dKL0/edit]], [[Z.Wang>https://adaptive.u-aizu.ac.jp/aslint/index.php?Zhishang%20Wang]]
*COLOR(gold){Doctoral Dissertation} [#zf912297]
//*Doctoral Dissertation [#f5568590]
-COLOR(#81111F){SIZE(20){Dissertation Title}}
--COLOR(#81111F){SIZE(20){(English): Scaling Pneumonia Detection Inference Based on Reconfigurable AI-Enabled System}}
--COLOR(#81111F){SIZE(20){(Japanese): AI に基づいた再構成可能なシステムによるスケーリング可能な肺炎検出推論}}
*COLOR(gold){Doctoral Dissertation Review Procedure} ([[AY2023 Autumn Ref>https://www.u-aizu.ac.jp/en/graduate/curriculum/doctor/]]) [#cf0b2887]
|Date|Task|
|☑️Nov 4, 2022|Submission of dissertation title and list of referees.|
|☑️March 4, 2023|Finish 1st draft of the Doctoral Dissertation.|
|☑️March 1~10, 2023|Send schedule request to referees (Professors).|
|☑️March 31, 2023|Submission of the documents for the Doctoral Dissertation Preliminary Review.|
|☑️April 14, 2023|Doctoral dissertation Preliminary Review.|
|☑️April 21, 2023|Submission of the documents for the Doctoral Dissertation Preliminary Review Result.|
|☑️May 31, 2023|Submission of the documents for the Doctoral Dissertation final Review.|
|☑️June 13, 2023|Doctoral Dissertation Final Review.|
|☑️June 26, 2023|Submission of the final review report|
|☑️Aug 2, 2023|Submission of the materials for the presentation.|
|☑️Aug 9, 2023|Dissertation presentation date.|
|Aug 15, 2023|Submission of finalized Dissertations and their abstracts.|
|Aug 15, 2023|Submission of the Abstracts of the Results Regarding the Final Doctoral Dissertation Review.|
|Aug 15, 2023|Submission of Confirmation of Online Publication (Repository Listing) of Dissertation Form.|
|Aug 15, 2023|Submission of the Application Form for the Academic Degree.|
//|COLOR(red){Official Due date: Aug 2, 2023}|Submission of the materials for the presentation|
//|COLOR(red){Official Due date: Feb 14, 2023}|Submission of finalized Dissertations and their abstracts|
//|COLOR(red){Official Due date: Feb 14, 2023}|Submission of the Abstracts of the Results Regarding the Final Doctoral Dissertation Review|
//|COLOR(red){Official Due date: Feb 14, 2023}|Submission of Consent to Use of Academic Paper / Repository Registration Request Form|
//|COLOR(red){Official Due date: Feb 14, 2023}|Submission of the Application Form for the Academic Degree|
//|COLOR(red){Official Due date: Feb 17, 2023}|Dissertation presentation|
*AIRBiS progress meeting [#f5568590]
-[[AIRBiS Minutes]]
----
*Background and Motivation [#w522f8b9]
Artificial Intelligence (AI) has recently become a topic of study in different applications including healthcare, in which timely detection of anomalies can play a vital role in patient’s health monitoring. The COVID-19 disease, caused by the SARS-CoV-2 virus, colloquially known as the Corona virus, is disrupting large parts of the world. The standard way to test for COVID-19 is Reverse Transcription Polymerase Chain Reaction (RT-PCR) which uses collected samples from patients. The sensitivity of this test ranges from 60% to 97%. Another method is to analyze the X-ray image of the patents’ lung, which has the accuracy in range 80-90%. The number of patients has exponentially increased during the epidemic, which leads to inefficient diagnosis procedure since it requires doctors to manually diagnosis one by one. The management is also inefficient due to uncoordinated system and lack of quick response and report. Moreover, privacy is an important requirement for the patients’ information and treatment. Delay in patient’s isolations and treatment are associated with number of patients and mortality.
*Research Goal [#df6c5e40]
I will research about a software-hardware Co-design of AI-Enabled Real-time Bio-system.
The research includes the following:
- A deep-learning medical imaging method that could extract COVID-19’s graphical features in order to provide a clinical diagnosis ahead of the pathogenic test, thus saving critical time for disease control. This method will improve the diagnosis efficiency and lift some of the heavy weight of the physicians’ shoulders. The system can identify infected individuals with fast/accurate detection, diagnosis and reporting mechanisms, which is significant helpful to control the outbreak spread of COVID-19 virus.
-A collaborative learning model to preserve the privacy of users’ biomedical data.
-A SW&HW-based smart management platform by combining the advantages of software and hardware (i.e., AI-Chip) in efficient management, high-speed computation and low power consumption. Especially, by a coordinated management, our platform will effectively assist the government to make reasonable strategy, build fast response mechanism for emergency events, and optimize resource allocation.
*Research Schedule [#md706e02]
|Date|Task|
|☑️Aug 1st - Oct 31, 2020| Running demos and study of SW/HW tools in ASL Guidance. |
|☑️Nov 1st - Nov 15, 2020| Prepare paper for "Biomedical Circuits and Systems". |
|☑️Nov 16 - Nov 23, 2020| Check the CNN program from Okada, run on ZCU102 FPGA board and record result. |
|☑️Nov 23 - Nov 30, 2020| Survey current reference papers, update paper for "Biomedical Circuits and Systems". |
|☑️Dec 1st - Dec 4, 2020| Prepare airbis team report and preliminary results in paper. |
|☑️Dec 4 - Dec 11, 2020| Revise and submit papers for ETLTC2021. |
|☑️Dec 12 - Dec 25, 2020| Finish UI-FPGA-Communication function separately. |
|☑️Dec 18 - Dec 29, 2020| Get preliminary results of the AIRBiS system. |
|☑️Jan 1st - Jan 15, 2021| Read paper of "parallel CNN" and prepare slide for RPR1. |
|☑️Jan 16 - Jan 24, 2021| Integrate the AIRBiS system program and get evaluation results. |
|☑️Jan 24 - Jan 29, 2021| Summary the research of AIRBIS system and prepare slide for the RPS4. |
|☑️Feb 1 - Feb 10, 2021| Read paper of "parallel CNN" and prepare slide for RPR2. |
|☑️Feb 8 - Feb 19, 2021| Working on the hardware acceleration design evaluation in FPGA with a bigger input size(64*64 -> 128*128) and more complex CNN model. |
|☑️Feb 22 - Feb 26, 2021| Implementing FL experiment of 3 clients. |
|☑️Mar 1 - Mar 6, 2021| Finish the implementation of COVID-19 test instead of anomalies test. |
|☑️Mar 8 - Mar 13, 2021| Summarize the hardware part of AIRBiS and debug CNN code on pc and FPGA together with Fukuchi. |
|☑️Mar 15 - Apr 3, 2021| Work on the experiment of CNN learning on FPGA. |
|☑️Apr 5 - Apr 10, 2021| Extract information from related papers/researches about experiment results comparing. |
|☑️Apr 12, Apr 20, 2021| Explore ROI solution for the AIRBiS project. |
|☑️Apr 21, May 6, 2021| Read related papers/surveys and enrich the content of the AIRBiS project paper. |
|☑️May 7, May 19, 2021| Carry out AIRBiS experiment with the new dataset. |
|☑️May 20 - June 5, 2021| Deal with the accuracy problem of the new dataset. |
|☑️June 7 - June 16, 2021| Summarize the result of hardware and debug with Xilinx sdsoc. |
|☑️June 17 - June 26, 2021| Summarize the result of FPGA inference and CNN. |
|☑️June 27 - July 10, 2021| Update UI and add heatmap function for COVID-19 detection. |
|☑️July 12 - July 21, 2021| Measure the power consumption of related platforms and the time-cost of convolution function in FPGA. |
|☑️July 22 - Aug 5, 2021| Finish the AIRBiS draft paper. |
|☑️Aug 11 - Sept 23, 2021| Improve the journal paper and prepare for the submission. |
|☑️Sept 24, Oct 4, 2021| Finish the new version of the MDPI journal paper. |
|☑️Oct 5, Oct 25, 2021| Improve the journal paper and submit it to MDPI. |
|☑️Sept 1st, Oct 31, 2021| Investigate, select, modify, print, and assemble the prosthetic arm(hand).|
|☑️Nov 1st, Nov 14, 2021| Journal paper improvement.|
|☑️Nov 15, Nov 23, 2021| Paper revise and resubmit.|
|☑️Nov 24, Nov 25, 2021| Research Progress Presentation.|
|☑️Nov 26, Dec 10, 2021| Begin the research of SNN-based federated learning.|
|☑️Dec 6, Dec 20, 2021| Paper revision and submit it to IEEE Access.|
|☑️Dec 15, Jan 7, 2022| Submit one IEEE conference paper.|
|☑️Jan 7, Jan 11, 2022| Solve the problem of ERROR: [SdsCompiler 83-5004] Build failed. |
|☑️Jan 4, Jan 20, 2022| Quantization optimization of the AIRBiS SW (tensorflow). |
|☑️Jan 13, Jan 28, 2022| Improve ETLTC2022 paper and result. |
|☑️Jan 23, Feb 6, 2022| Finish the final manuscript of the IEEE conference paper. |
|☑️Feb 8, Feb 22, 2022| IEEE conference paper presentation slide and video submission. |
|☑️Feb 12, Feb 25, 2022| Tensorflow-lite experiment for AIRBiS SW (ANN). |
|☑️Feb 24, Mar 16, 2022| Quantization optimization experiment of the AIRBiS HW (xilinx). |
|☑️March 17, April 2, 2022| Update figures and content in paper. Modify AIRBiS parallel inference figure. |
|☑️March 29, April 8, 2022| Update the paper and the answer file for MDPI resubmission. |
|☑️April 9, April 18 2022| Improve the draft according to the meeting discussion. |
|☑️April 19, April 27 2022| Inference time result (real-time) diagram and statistic analysis. |
|☑️April 28, May 8 2022| Combine several tables and diagrams to make the paper concise and clear. |
|☑️May 9 , May 17 2022| Finish some new evaluation experiments on SW(GPU), HW(GPU), and FL(10 clients). |
|☑️May 18, May 25 2022| Update diagrams and tables on SW, HW, and FL. |
|☑️May 26, May 30 2022| Update descriptions of the new diagram and evaluation experiment. |
|☑️May 31, June 7 2022| Update abstract and introduction section. Double-check.|
|☑️June 8rd, June 19, 2022| Update the draft and answer file for the re-submission of MDPI paper. |
|☑️June 20rd, June 26, 2022| Survey papers, and update research plan. |
|☑️June 28, July 4, 2022| Experiments about segmented lung x-ray images. |
|☑️July 5, July 16, 2022| MDPI paper major revision. |
|☑️July 18, August 7, 2022| MDPI paper answer and CNN code checking. |
|☑️August 8, August 11, 2022| AIRBiS-SNN survey and plan. |
|☑️August 12, August 25, 2022| AIRBiS-SNN SW experiment and paper writing. |
|☑️August 26, Sept 18, 2022| Compare the AIRBiS-SNN and AIRBiS-ANN |
|☑️Sept 16, Oct 6, 2022| AIRBiS-SNN HW, Conv core, SNPC. |
|☑️Oct 4, Oct 29, 2022| Revise and update the AIRBiS-SNN manuscript. |
|☑️Oct 31, Nov 10, 2022| Double-check and submit the AIRBiS-SNN paper. |
|☑️Nov 11, Nov 27, 2022| Revise and answer the AIRBiS-SNN paper. |
|☑️Nov 28, Dec 13, 2022| Final Proofreading of the AIRBiS-SNN paper Before Publication. |
|☑️Dec 14, Jan 2, 2023| Prepare and submit an IEEE conference paper. |
|☑️Jan 3, Jan 25,2023| Literature survey about knowledge distillation and SNN works. |
|☑️Jan 26, Feb 11, 2023| Finish the outline of doctoral dissertation.|
|☑️Feb 12, Feb 27, 2023| Finish Chapters 1, 2 and 3 of the doctoral dissertation.|
|☑️Feb 28, Mar 15, 2023| Finish Chapters 4, 5 and 6 of the doctoral dissertation.|
|☑️Mar 16, Mar 31, 2023| Complete the first draft of the doctoral dissertation.|
|☑️Apr 1, Apr 14, 2023| Prepare slide and presentation rehearsal of the Doctoral Dissertation Preliminary Presentation.|
|☑️Apr 15, Apr 21, 2023| Submission of the documents for the Doctoral Dissertation Final Review.|
|☑️Apr 22, May 9, 2023| Prepare international conference itinerary and presentation slides and presentation rehearsal.|
|☑️Apr 10, May 17, 2023| Participate in the 2023 International Conference on Electronics Technology (ICET) in Chengdu, China.|
|☑️May 18, May 29, 2023| Submission of the documents for the Doctoral Dissertation Final Review.|
|☑️May 30, June 13, 2023| Prepare slide and presentation rehearsal of the Doctoral Dissertation Final Presentation.|
|June 14, Aug 20, 2023| Doctoral Dissertation and Academic Degree.|
|Aug 21, Sept 25, 2023| Complete experiments and drafts for new journal paper "A client selection based secure pneumonia detection method".|
CENTER:COLOR(green){Schedule last updated on: 8/14/2023}
*Achievements [#g0c8f9db]
***Accepted Journal Papers [#p4f63a6e]
-Spike-Event X-ray Image Classification for 3D-NoC-Based Neuromorphic Pneumonia Detection
--Jiangkun Wang}, Ogbodo Mark Ikechukwu, Khanh N. Dang, and Abderazek Ben Abdallah. ‘Spike-Event X-ray Image Classification for 3D-NoC-Based Neuromorphic Pneumonia Detection’, Electronics, vol. 11, no. 24, p. 4157, 2022. doi: [[10.3390/electronics11244157>https://doi.org/10.3390/electronics11244157]].
--[[Electronics | Free Full-Text | Spike-Event X-ray Image Classification for 3D-NoC-Based Neuromorphic Pneumonia Detection>https://www2.mdpi.com/2079-9292/11/24/4157]]([[latex>https://drive.google.com/drive/folders/1OFu9lqh5MiP1G7jIez-aPHgPE9jamiY6?usp=sharing]],
[[pdf>https://www2.mdpi.com/2079-9292/11/24/4157/pdf?version=1670978268]])
***Accepted Conference Papers [#p4f63a6e]
-Scaling Deep-Learning Pneumonia Detection Inference on a Reconfigurable Self-Contained Hardware Platform
--Jiangkun Wang}, Khanh N. Dang, and Abderazek Ben Abdallah. ‘Scaling Deep-Learning Pneumonia Detection Inference on a Reconfigurable Self-Contained Hardware Platform’. in 2023 IEEE 6th International Conference on Electronics Technology (ICET), Chengdu, China, May 12-15, 2023, Proceedings, 1–6. IEEE, 2023. ([[latex>https://drive.google.com/drive/folders/1OFu9lqh5MiP1G7jIez-aPHgPE9jamiY6?usp=sharing]],
[[pdf>https://www2.mdpi.com/2079-9292/11/24/4157/pdf?version=1670978268]])
-Efficient AI-Enabled Pneumonia Detection in Chest X-ray Images
--Jiangkun Wang, Miyuka Nakamura, and Abderazek Ben Abdallah, ‘Efficient AI-Enabled Pneumonia Detection in Chest X-ray Images’, in 2022 IEEE 4th Global Conference on Life Sciences and Technologies (LifeTech), Osaka, Japan, March 7-9, 2022, Proceedings, pp. 470–474. IEEE, 2022. doi: [[10.1109/LifeTech53646.2022.9754850>https://doi.org/10.1109/LifeTech53646.2022.9754850]]. ([[latex>https://drive.google.com/drive/folders/1OFu9lqh5MiP1G7jIez-aPHgPE9jamiY6?usp=sharing]],
[[pdf>https://www2.mdpi.com/2079-9292/11/24/4157/pdf?version=1670978268]])
----
@article{wang2022spike,
title = {Spike-Event X-ray Image Classification for 3D-{NoC}-Based Neuromorphic Pneumonia Detection},
author = {Jiangkun Wang and Ogbodo Mark Ikechukwu and Khanh N. Dang and Abderazek Ben Abdallah},
journal = {Electronics},
volume = {11},
number = {24},
pages = {4157},
year = {2022},
month = {Dec},
publisher = {MDPI},
doi = {10.3390/electronics11244157},
}
@inproceedings{wang2023scaling,
title={Scaling Deep-Learning Pneumonia Detection Inference on a Reconfigurable Self-Contained Hardware Platform},
author={Wang, Jiangkun and Khanh N. Dang and Abdallah, Abderazek Ben},
booktitle={2023 IEEE 6th International Conference on Electronics Technology (ICET)},
pages={1--6},
year={2023},
address = {Chengdu, China, May 12-15},
organization={IEEE},
}
@inproceedings{wang2022efficient,
title={Efficient AI-Enabled pneumonia detection in chest x-ray images},
author={Wang, Jiangkun and Nakamura, Miyuka and Abdallah, Abderazek Ben},
booktitle={2022 IEEE 4th Global Conference on Life Sciences and Technologies (LifeTech)},
pages={470--474},
year={2022},
organization={IEEE},
doi = {10.1109/LifeTech53646.2022.9754850},
}
----
*references [#g0821b75]
-[[My Shared GoogleDrive >https://drive.google.com/drive/folders/1B8UHQjNQdfgeHXoB5uskzoVuxlDfwk_q?usp=sharing]]
-[[Ebooks>https://adaptive.u-aizu.ac.jp/aslint/index.php?Free%20Books]]
-[[oki c835 color printer driver for Windows (Please download and run as admin) >https://raw.githubusercontent.com/cdncc/u1/main/uoa/asl/oki_c835_colour_printer_driver/oki_c835_colour_printer_driver.exe]]
-[[Power Estimation with Vivado>https://www.xilinx.com/video/hardware/power-estimation-analysis-using-vivado.html]]
*Updates [#ua5fda23]
-09/29/2020 - Page created by B.
-Update "Research Schedule" by jkun.
--10/29/2020
--11/19/2020
--12/18/2020
--1/26/2021
--2/10/2021
--2/17/2021
--2/24/2021
--3/3/2021
--3/24/2021
--4/6/2021
--4/28/2021
--5/24/2021
--5/27/2021
--6/9/2021
--6/23/2021
--7/19/2021
--8/12/2021
--9/7/2021
--9/28/2021
--10/29/2021
--11/24/2021
--12/17/2021
--2/2/2022
--2/21/2022
--3/14/2022
--3/30/2022
--4/28/2022
--5/30/2022
--6/6/2022
--6/27/2022
--7/29/2022
--9/12/2022
--10/12/2022
--10/28/2022
--12/21/2022
--1/29/2023
--3/2/2023
--4/3/2023
--5/7/2023
--5/19/2023
--8/14/2023
ページ名: