415 citations · 1.2k across the 53 of their papers we have counts for
7 papers · 1 filter
Competing Ratio Loss for Discriminative Multi-class Image Classification
Ke Zhang, Yurong Guo, Xinsheng Wang +4
The development of deep convolutional neural network architecture is critical to the improvement of image classification task performance. Many image classification studies use dee…
Semi-Heterogeneous Three-Way Joint Embedding Network for Sketch-Based Image Retrieval
Jianjun Lei, Yuxin Song, Bo Peng +3
Sketch-based image retrieval (SBIR) is a challenging task due to the large cross-domain gap between sketches and natural images. How to align abstract sketches and natural images i…
Competing Ratio Loss for Discriminative Multi-class Image Classification
Ke Zhang, Xinsheng Wang, Yurong Guo +3
The development of deep convolutional neural network architecture is critical to the improvement of image classification task performance. A lot of studies of image classification…
Deep Zero-Shot Learning for Scene Sketch
Yao Xie, Peng Xu, Zhanyu Ma
We introduce a novel problem of scene sketch zero-shot learning (SSZSL), which is a challenging task, since (i) different from photo, the gap between common semantic domain (e.g.,…
Channel Max Pooling Layer for Fine-Grained Vehicle Classification
Zhanyu Ma, Dongliang Chang, Xiaoxu Li
Deep convolutional networks have recently shown excellent performance on Fine-Grained Vehicle Classification. Based on these existing works, we consider that the back-probation alg…
On the Convergence of Extended Variational Inference for Non-Gaussian Statistical Models
Zhanyu Ma, Jalil Taghia, Jun Guo
Variational inference (VI) is a widely used framework in Bayesian estimation. For most of the non-Gaussian statistical models, it is infeasible to find an analytically tractable so…
Vehicular Edge Computing via Deep Reinforcement Learning
Qi Qi, Zhanyu Ma
The smart vehicles construct Vehicle of Internet which can execute various intelligent services. Although the computation capability of the vehicle is limited, multi-type of edge c…