Binary Neural Networks: Algorithms, Architectures, and Applications
暫譯: 二元神經網絡：演算法、架構與應用

我們的書籍將介紹網路附加儲存（NAS），因為它在各種應用中，如影像分類和物件偵測，具有卓越的性能和最先進的技術。

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.

包昌章教授是中國北京航空航天大學人工智慧研究所的全職教授。他被中國教育部的新世紀優秀人才計畫選中，並擔任百度公司的深度學習實驗室學術顧問，以及浙江省北京航空航天大學杭州研究所的傑出研究員。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方法是最先進的特徵描述子，分別在Google Scholar上獲得了1234和768次引用。這兩項研究都是「時代考驗」的作品。我們的1位元方法在ImageNet上達到了最佳性能。他的團隊還贏得了ECCV 2020微小物體檢測、COCO物體檢測和ICPR 2020花粉識別挑戰賽。

徐晟於中國北京航空航天大學獲得汽車工程學士學位。目前，他是北京航空航天大學自動化科學與電氣工程學院的博士生，專攻計算機視覺、模型量化和壓縮。他在該領域做出了重要貢獻，作為第一作者在CVPR、ECCV、NeurIPS、AAAI、BMVC、IJCV和ACM TOMM等頂級會議和期刊上發表了約十篇論文。值得注意的是，他有4篇論文被這些著名會議選為口頭報告或重點展示。此外，徐晟積極參與學術社群，擔任多個國際期刊和會議的審稿人，包括CVPR、ICCV、ECCV、NeurIPS、ICML和IEEE TCSVT。他的專業知識也使他的團隊在ECCV 2020微小物體檢測挑戰賽中獲勝。

林名寶於2022年在中國廈門大學完成碩士-博士學位，獲得智能科學與技術博士學位。早前，他於2016年在中國福州大學獲得學士學位。目前，他是中國上海騰訊優圖實驗室的高級研究員。他在頂級會議/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以及信息檢索。

王天成於中國北京航空航天大學獲得自動化學士學位。目前，他正在北京航空航天大學人工智慧研究所攻讀博士學位。在本科期間，他連續幾年獲得優秀學生稱號，並獲得各種獎學金，包括學業優秀獎學金和學術競賽獎學金等。他參與了幾個人工智慧項目，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，目標是探索高能效模型並推動神經網絡在嵌入式設備中的部署。

大衛·多曼博士是布法羅大學（UB）帝國創新教授及布法羅大學人工智慧研究所所長。在來到UB之前，他曾是國防高級研究計畫局（DARPA）的項目經理，負責開發、選擇和監督約1.5億美元的計算機視覺、人類語言技術和語音分析等領域的研究和轉型資金。他協調所有項目的執行者，促進共識，評估跨團隊管理並監督流暢的項目目標。