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Knowledge Distillation in Computer Vision

by Linfeng Zhang
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Current price ₹4,003.00
Original price ₹6,158.00
Original price ₹6,158.00
Original price ₹6,158.00
(-35%)
₹4,003.00
Current price ₹4,003.00

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Book cover type: Paperback
  • ISBN13: 9789819503667
  • Binding: Paperback
  • Subject: N/A
  • Publisher: Springer
  • Publisher Imprint: Springer
  • Publication Date:
  • Pages: 140
  • Original Price: EUR 54.49
  • Language: English
  • Edition: N/A
  • Item Weight: 223 grams
  • BISAC Subject(s): Artificial Intelligence / Computer Vision & Pattern Recognition

Dr. Zhang Linfeng is the assistant professor in School of Artificial Intellignce, Shanghai Jiao Tong University. He graduated from the Institute of Interdisciplinary Information Sciences at Tsinghua University with a doctoral degree in Computer Science and Technology, specializing in computer vision model compression and acceleration. His doctoral dissertation, "Structured Knowledge Distillation: Towards Efficient Visual Intelligence," was recognized as an outstanding doctoral dissertation by Tsinghua University. He has served as a reviewer for more than a dozen top academic conferences and journals, including IEEE TPAMI, NeurIPS, ICLR, and CVPR for several consecutive years. He has published more than 20 high-level academic papers as first author or corresponding author. According to Google Scholar, his papers have been cited 2,300 times, with the highest citation count for a single first-authored paper exceeding 1,000 times. At the 2019 ICCV conference, he first proposed the Self-Distillation algorithm, which is one of the representative works in the field of knowledge distillation. He has successfully applied knowledge distillation algorithms to various visual tasks such as object detection, instance segmentation, and image generation, as well as to different types of visual data including images, multi-view images, point clouds, and videos to achieve compression and acceleration effects of visual models. Meanwhile, his research achievements have been utilized in the Qiming series chips developed by Polar Bear Technology, Huawei, DiD Global, and Kwai, providing compression and acceleration effects for artificial intelligence models in real industrial scenarios.

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