标题
Modeling Cardinality in Image Hashing
作者
关键词
-
出版物
IEEE Transactions on Cybernetics
Volume 53, Issue 1, Pages 114-123
出版商
Institute of Electrical and Electronics Engineers (IEEE)
发表日期
2021-07-09
DOI
10.1109/tcyb.2021.3089879
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- Discrete Deep Hashing With Ranking Optimization for Image Retrieval
- (2019) Xiaoqiang Lu et al. IEEE Transactions on Neural Networks and Learning Systems
- Adaptive Hashing With Sparse Matrix Factorization
- (2019) Huawen Liu et al. IEEE Transactions on Neural Networks and Learning Systems
- Bidirectional Discrete Matrix Factorization Hashing for Image Search
- (2019) Shiyuan He et al. IEEE Transactions on Cybernetics
- Transfer Hashing: From Shallow to Deep
- (2018) Joey Tianyi Zhou et al. IEEE Transactions on Neural Networks and Learning Systems
- Error Correcting Input and Output Hashing
- (2018) Chao Ma et al. IEEE Transactions on Cybernetics
- Graph Convolutional Network Hashing
- (2018) Xiang Zhou et al. IEEE Transactions on Cybernetics
- Latent Semantic Minimal Hashing for Image Retrieval
- (2017) Xiaoqiang Lu et al. IEEE TRANSACTIONS ON IMAGE PROCESSING
- Unsupervised Topic Hypergraph Hashing for Efficient Mobile Image Retrieval
- (2017) Lei Zhu et al. IEEE Transactions on Cybernetics
- Hashing on Nonlinear Manifolds
- (2015) Fumin Shen et al. IEEE TRANSACTIONS ON IMAGE PROCESSING
- Neighborhood Discriminant Hashing for Large-Scale Image Retrieval
- (2015) Jinhui Tang et al. IEEE TRANSACTIONS ON IMAGE PROCESSING
- Semi-Supervised Hashing for Large-Scale Search
- (2012) Jun Wang et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- LDAHash: Improved Matching with Smaller Descriptors
- (2011) C. Strecha et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Kernelized Locality-Sensitive Hashing
- (2011) B. Kulis et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Near-optimal hashing algorithms for approximate nearest neighbor in high dimensions
- (2008) Alexandr Andoni et al. COMMUNICATIONS OF THE ACM
Add your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload NowAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started