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Found 7 papers, 0 papers with code
Self-supervised Training Sample Difficulty Balancing for Local Descriptor Learning
In the case of an imbalance between positive and negative samples, hard negative mining strategies have been shown to help models learn more subtle differences between positive and negative samples, thus improving recognition performance.
Interval Type-2 Fuzzy Neural Networks for Multi-Label Classification
We also propose a loss function to measure the similarities between binary labels in datasets and interval type-2 fuzzy memberships generated by our model.
Coupled Learning for Facial Deblur
In this paper, we represent point spread functions (PSFs) by the linear combination of a set of pre-defined orthogonal PSFs, and similarly, an estimated intrinsic (EI) sharp face image is represented by the linear combination of a set of pre-defined orthogonal face images.
Global Hashing System for Fast Image Search
Our methods are based on finding the tradeoff between the information losses in these two steps.
Learning Decorrelated Hashing Codes for Multimodal Retrieval
As the output of sigmoid function approximates a binary code matrix, the proposed MCR can efficiently decorrelate the hashing codes.
A survey on trajectory clustering analysis
This paper comprehensively surveys the development of trajectory clustering.
Semi-supervised Multimodal Hashing
As unsupervised multimodal hashing methods are usually inferior to supervised ones, while the supervised ones requires too much manually labeled data, the proposed method in this paper utilizes a part of labels to design a semi-supervised multimodal hashing method.
