Anchor-based self-ensembling for semi-supervised deep pairwise hashing

DOI10.1007/s11263-020-01299-xzbMath1483.68347OpenAlexW3007196254MaRDI QIDQ2056149

Lin Yang, Xiaoshuang Shi, Fuyong Xing, Yun Liang, Zhen-Hua Guo

Publication date: 1 December 2021

Published in: International Journal of Computer Vision (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11263-020-01299-x

zbMATH Keywords

semi-supervisedanchordeep pairwise hashingself-ensembling

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Coding and information theory (compaction, compression, models of communication, encoding schemes, etc.) (aspects in computer science) (68P30) Data structures (68P05)

Uses Software

• CIFAR
• ImageNet
• Adam
• t-SNE
• NUS-WIDE
• GitHub
• MS-COCO
• AlexNet

Cites Work

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• Min-wise independent permutations
• Bit-Scalable Deep Hashing With Regularized Similarity Learning for Image Retrieval and Person Re-Identification
• Self-Supervised Video Hashing With Hierarchical Binary Auto-Encoder
• Deep Discrete Supervised Hashing
• Semi-Supervised Metric Learning-Based Anchor Graph Hashing for Large-Scale Image Retrieval
• Locality-sensitive hashing scheme based on p-stable distributions
• Modeling the shape of the scene: A holistic representation of the spatial envelope

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