{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T13:01:26Z","timestamp":1784120486877,"version":"3.55.0"},"reference-count":167,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2025,10,18]],"date-time":"2025-10-18T00:00:00Z","timestamp":1760745600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the National Natural Science Foundation of China under Grant","award":["61801319"],"award-info":[{"award-number":["61801319"]}]},{"name":"the Sichuan Science and Technology Program under Grant","award":["2020JDJQ0061 and 2021YFG0099"],"award-info":[{"award-number":["2020JDJQ0061 and 2021YFG0099"]}]},{"name":"the Opening Project of Artificial Intelligence Key Laboratory of Sichuan Province under Grant","award":["2021RZJ01"],"award-info":[{"award-number":["2021RZJ01"]}]},{"name":"the Scientific Research and Innovation Team Program of Sichuan University of Science and Engineering under Grant","award":["SUSE652A011"],"award-info":[{"award-number":["SUSE652A011"]}]},{"name":"the Postgraduate Innovation Fund Project of Sichuan University of Science and Engineering under Grant","award":["Y2025081"],"award-info":[{"award-number":["Y2025081"]}]},{"name":"the Exploration and Practice of the Path to Improve the Quality of Master's Degree Cultivation of Electronic Information Students Empowered by Numerical Intelligence","award":["JG202405"],"award-info":[{"award-number":["JG202405"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>As the complexity of convolutional neural networks (CNN) continues to increase, efficient deployment on computationally constrained hardware platforms has become a significant challenge. Against this backdrop, field-programmable gate arrays (FPGA) emerge as an up-and-coming CNN acceleration platform due to their inherent energy efficiency, reconfigurability, and parallel processing capabilities. This paper establishes a systematic analytical framework to explore CNN optimization strategies on FPGA from both algorithmic and hardware perspectives. It emphasizes co-design methodologies between algorithms and hardware, extending these concepts to other embedded system applications. Furthermore, the paper summarizes current performance evaluation frameworks to assess the effectiveness of acceleration schemes comprehensively. Finally, building upon existing work, it identifies key challenges in this field and outlines future research directions.<\/jats:p>","DOI":"10.3390\/info16100914","type":"journal-article","created":{"date-parts":[[2025,10,20]],"date-time":"2025-10-20T13:54:41Z","timestamp":1760968481000},"page":"914","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Convolutional Neural Network Acceleration Techniques Based on FPGA Platforms: Principles, Methods, and Challenges"],"prefix":"10.3390","volume":"16","author":[{"given":"Li","family":"Gao","sequence":"first","affiliation":[{"name":"School of Automation and Information Engineering, Sichuan University of Science and Engineering, Yibin 644000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1767-1831","authenticated-orcid":false,"given":"Zhongqiang","family":"Luo","sequence":"additional","affiliation":[{"name":"School of Automation and Information Engineering, Sichuan University of Science and Engineering, Yibin 644000, China"},{"name":"Intelligent Perception and Control Key Laboratory of Sichuan Province, Sichuan University of Science and Engineering, Yibin 644000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lin","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Automation and Information Engineering, Sichuan University of Science and Engineering, Yibin 644000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,10,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Hu, Y., Liu, Y., and Liu, Z. 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