While stochastic gradient descent (SGD) is still the most popular
optimi...
Identifying moving objects is an essential capability for autonomous sys...
While Named Entity Recognition (NER) is a widely studied task, making
in...
Multi-task learning (MTL) aims to improve the generalization performance...
Unsupervised image hashing, which maps images into binary codes without
...
Many unanswerable adversarial questions fool the question-answer (QA) sy...
In this paper, we study an adaptive planewave method for multiple eigenv...
Caricature is an artistic representation that deliberately exaggerates t...
Low precision training is one of the most popular strategies for deployi...
In recent years, deep-networks-based hashing has become a leading approa...
In this paper, we focus on triplet-based deep binary embedding networks ...
Recently, deep-networks-based hashing (deep hashing) has become a leadin...
Face age progression, which aims to predict the future looks, is importa...
As the rapid growth of multi-modal data, hashing methods for cross-modal...
Zero-shot Hashing (ZSH) is to learn hashing models for novel/target clas...
Similarity-preserving hashing is a widely-used method for nearest neighb...
We describe an attentive encoder that combines tree-structured recursive...
Similarity-preserving hashing is a widely-used method for nearest neighb...
In order to track the moving objects in long range against occlusion,
in...