Feature Quantization
Feature Quantization is a method in image feature engineering that discretizes continuous feature representations into a finite set of discrete values or bins to reduce dimensionality and enhance computational efficiency while preserving discriminative information.
414
Publications
32.2K
Citations
1.2K
Authors
455
Institutions
Publications per year
2017–2026
159
Parents
414
Scalable Recognition with a Vocabulary Tree
D. Nistér, Henrik Stewénius · 2006 · 3.6K citations
Lost in quantization: Improving particular object retrieval in large scale image databases
James Philbin, Ondřej Chum, Michael Isard et al. · 2008 · 1.5K citations
Shape Quantization and Recognition with Randomized Trees
Yali Amit, Donald Geman · Neural Computation · 1997 · 1.3K citations
Quantized Convolutional Neural Networks for Mobile Devices
Jiaxiang Wu, Cong Leng, Yuhang Wang et al. · 2016 · 1.3K citations
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455
Tsinghua University
Beijing, China
15 h-index
57 publications
3.9K citations

Chinese Academy of Sciences
Beijing, China
12 h-index
42 publications
7.7K citations
Nanyang Technological University
Singapore, Singapore
11 h-index
25 publications
3K citations
University of Chinese Academy of Sciences
Beijing, China
11 h-index
33 publications
1.5K citations
Hochschule Mittweida
Mittweida, Germany
9 h-index
20 publications
475 citations

Peking University
Beijing, China
9 h-index
17 publications
670 citations
University of Science and Technology of China
Hefei, China
8 h-index
17 publications
759 citations

University of Electronic Science and Technology of China
Chengdu, China
7 h-index
24 publications
901 citations
1–8 of 455
Repository · 27 publications · 2.6K citations
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21 publications · 646 citations
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16 publications · 1.1K citations
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TPAMI · 9 publications · 587 citations
9
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9 publications · 354 citations
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