415 citations · 750 across the 20 of their papers we have counts for
6 papers · 1 filter
DS-UI: Dual-Supervised Mixture of Gaussian Mixture Models for Uncertainty Inference
Jiyang Xie, Zhanyu Ma, Jing-Hao Xue +2
This paper proposes a dual-supervised uncertainty inference (DS-UI) framework for improving Bayesian estimation-based uncertainty inference (UI) in deep neural network (DNN)-based…
Advanced Dropout: A Model-free Methodology for Bayesian Dropout Optimization
Jiyang Xie, Zhanyu Ma, and Jianjun Lei +4
Due to lack of data, overfitting ubiquitously exists in real-world applications of deep neural networks (DNNs). We propose advanced dropout, a model-free methodology, to mitigate o…
GPCA: A Probabilistic Framework for Gaussian Process Embedded Channel Attention
Jiyang Xie, Dongliang Chang, Zhanyu Ma +2
Channel attention mechanisms have been commonly applied in many visual tasks for effective performance improvement. It is able to reinforce the informative channels as well as to s…
Fine-Grained Visual Classification via Progressive Multi-Granularity Training of Jigsaw Patches
Ruoyi Du, Dongliang Chang, Ayan Kumar Bhunia +4
Fine-grained visual classification (FGVC) is much more challenging than traditional classification tasks due to the inherently subtle intra-class object variations. Recent works ma…
Weakly Supervised Attention Pyramid Convolutional Neural Network for Fine-Grained Visual Classification
Yifeng Ding, Shaoguo Wen, Jiyang Xie +4
Classifying the sub-categories of an object from the same super-category (e.g. bird species, car and aircraft models) in fine-grained visual classification (FGVC) highly relies on…
The Devil is in the Channels: Mutual-Channel Loss for Fine-Grained Image Classification
Dongliang Chang, Yifeng Ding, Jiyang Xie +6
Key for solving fine-grained image categorization is finding discriminate and local regions that correspond to subtle visual traits. Great strides have been made, with complex netw…