Binary Neural Networks: Algorithms, Architectures, and Applications

我們的書籍還將介紹NAS，因為它在各種應用中具有卓越的優勢和最先進的性能，例如圖像分類和物體檢測。

Baochang Zhang is a full Professor with Institute of Artificial Intelligence, Beihang University, Beijing, China. He was selected by the Program for New Century Excellent Talents in University of Ministry of Education of China, also selected as Academic Advisor of Deep Learning Lab of Baidu Inc., and a distinguished researcher of Beihang Hangzhou Institute in Zhejiang Province. His research interests include explainable deep learning, computer vision and patter recognition. His HGPP and LDP methods were state-of-the-art feature descriptors, with 1234 and 768 Google Scholar citations, respectively. Both are "Test-of-Time" works. Our 1-bit methods achieved the best performance on ImageNet. His group also won the ECCV 2020 tiny object detection, COCO object detection, and ICPR 2020 Pollen recognition challenges.

Sheng Xu received the B.E. degree in Automotive Engineering from Beihang University, Beijing, China. He is currently a Ph.D. with the school of Automation Science and Electrical Engineering, Beihang University, Beijing, China, specializing in computer vision, model quantization, and compression. He has made significant contributions to the field and has published about a dozen papers as the first author in top-tier conferences and journals such as CVPR, ECCV, NeurIPS, AAAI, BMVC, IJCV, and ACM TOMM. Notably, he has 4 papers selected as oral or highlighted presentations by these prestigious conferences. Furthermore, Sheng Xu actively participates in the academic community as a reviewer for various international journals and conferences, including CVPR, ICCV, ECCV, NeurIPS, ICML, and IEEE TCSVT. His expertise has also led to his group's victory in the ECCV 2020 tiny object detection challenge.

Mingbao Lin finished his M.S.-Ph.D. study and obtained the Ph.D. degree in intelligence science and technology from Xiamen University, Xiamen, China, in 2022. Earlier, he received the B.S. degree from Fuzhou University, Fuzhou, China, in 2016. He is currently a senior researcher with the Tencent Youtu Lab, Shanghai, China. His publications on top-tier conferences/journals include IEEE TPAMI, IJCV, IEEE TIP, IEEE TNNLS, CVPR, NeurIPS, AAAI, IJCAI, ACM MM and so on. His current research interest is to develop efficient vision model, as well as information retrieval.

Tiancheng Wang received the B.E. degree in Automation from Beihang University, Beijing, China. He is currently pursuing the Ph.D. degree with the school of Institute of Artificial Intelligence, Beihang University, Beijing, China. During undergraduate, he has been awarded the title of Merit Student for several consecutive years, and has received various scholarships including academic excellence scholarship and academic competitions scholarship, etc. He was involved in several AI projects, including behavior detection and intention understanding research and unmanned air-based vision platform, etc. Now, his current research interests include deep learning and network compression, his goal is to explore the highly energy-saving model and drive the deployment of neural networks in embedded devices.

Dr. David Doermann is a Professor of Empire Innovation at the University at Buffalo (UB) and the Director of the University at Buffalo Artificial Intelligence Institute. Prior to coming to UB, he was a program manager at the Defense Advanced Research Projects Agency (DARPA), where he developed, selected and oversaw approximately $150 million in research and transition funding in the areas of computer vision, human language technologies and voice analytics. He coordinated performers on all of the projects, orchestrating consensus, evaluating cross team management and overseeing fluid program objectives.

張寶昌是中國北京北航大學人工智能研究所的教授。他被中國教育部新世紀優秀人才計劃選中，並被百度深度學習實驗室選為學術顧問，同時也是北航杭州研究院的傑出研究員。他的研究興趣包括可解釋的深度學習、計算機視覺和模式識別。他的HGPP和LDP方法是當時最先進的特徵描述子，分別在Google Scholar上引用了1234和768次。這兩個方法都是“經得起時間考驗”的作品。他的1位元方法在ImageNet上取得了最佳性能。他的團隊還贏得了ECCV 2020微小目標檢測、COCO目標檢測和ICPR 2020花粉識別挑戰。

徐晟在北京北航大學獲得汽車工程學士學位，目前在北航自動化科學與電氣工程學院攻讀博士學位，專攻計算機視覺、模型量化和壓縮。他在領先的會議和期刊上以第一作者身份發表了十幾篇論文，包括CVPR、ECCV、NeurIPS、AAAI、BMVC、IJCV和ACM TOMM等。值得注意的是，他的4篇論文被這些知名會議選為口頭報告或重點報告。此外，徐晟還積極參與學術界，擔任CVPR、ICCV、ECCV、NeurIPS、ICML和IEEE TCSVT等國際期刊和會議的審稿人。他的專業知識也使他的團隊在ECCV 2020微小目標檢測挑戰中獲勝。

林明寶在廈門大學智能科學與技術專業完成碩士博士學位，並於2022年獲得博士學位。他在2016年從福州大學獲得學士學位。目前，他是騰訊優圖實驗室的高級研究員。他在頂級會議和期刊上的發表包括IEEE TPAMI、IJCV、IEEE TIP、IEEE TNNLS、CVPR、NeurIPS、AAAI、IJCAI、ACM MM等。他目前的研究興趣是開發高效的視覺模型和信息檢索。

王天成在北京北航大學獲得自動化學士學位，目前在北航人工智能研究所攻讀博士學位。在本科期間，他連續多年獲得優秀學生稱號，並獲得多項獎學金，包括學術優秀獎學金和學術競賽獎學金等。他參與了多個人工智能項目，包括行為檢測和意圖理解研究以及無人機視覺平台等。現在，他的研究興趣包括深度學習和網絡壓縮，他的目標是探索高度節能的模型，推動神經網絡在嵌入式設備上的部署。

David Doermann博士是紐約州立大學水牛城分校的帝國創新教授，也是該校人工智能研究所的所長。在加入紐約州立大學之前，他曾在國防高級研究計劃局（DARPA）擔任項目經理，負責計算機視覺、人類語言技術和語音分析等領域的約1.5億美元的研究和轉化資金。他協調了所有項目的執行者，協調共識，評估跨團隊管理並監督流動的項目目標。