481 citations · 1.3k across the 30 of their papers we have counts for
4 papers · 1 filter
Sparse DNNs with Improved Adversarial Robustness
Yiwen Guo, Chao Zhang, Changshui Zhang +1
Deep neural networks (DNNs) are computationally/memory-intensive and vulnerable to adversarial attacks, making them prohibitive in some real-world applications. By converting dense…
Object Detection from Scratch with Deep Supervision
Zhiqiang Shen, Zhuang Liu, Jianguo Li +3
We propose Deeply Supervised Object Detectors (DSOD), an object detection framework that can be trained from scratch. Recent advances in object detection heavily depend on the off-…
Network Decoupling: From Regular to Depthwise Separable Convolutions
Jianbo Guo, Yuxi Li, Weiyao Lin +2
Depthwise separable convolution has shown great efficiency in network design, but requires time-consuming training procedure with full training-set available. This paper first anal…
Learning Visual Knowledge Memory Networks for Visual Question Answering
Zhou Su, Chen Zhu, Yinpeng Dong +3
Visual question answering (VQA) requires joint comprehension of images and natural language questions, where many questions can't be directly or clearly answered from visual conten…