142 citations · 321 across the 31 of their papers we have counts for
6 papers · 1 filter
Towards Better Forecasting by Fusing Near and Distant Future Visions
Jiezhu Cheng, Kaizhu Huang, Zibin Zheng
Multivariate time series forecasting is an important yet challenging problem in machine learning. Most existing approaches only forecast the series value of one future moment, igno…
Deep Minimax Probability Machine
Lirong He, Ziyi Guo, Kaizhu Huang +1
Deep neural networks enjoy a powerful representation and have proven effective in a number of applications. However, recent advances show that deep neural networks are vulnerable t…
Reliability Does Matter: An End-to-End Weakly Supervised Semantic Segmentation Approach
Bingfeng Zhang, Jimin Xiao, Yunchao Wei +2
Weakly supervised semantic segmentation is a challenging task as it only takes image-level information as supervision for training but produces pixel-level predictions for testing.…
On Model Robustness Against Adversarial Examples
Shufei Zhang, Kaizhu Huang, Zenglin Xu
We study the model robustness against adversarial examples, referred to as small perturbed input data that may however fool many state-of-the-art deep learning models. Unlike previ…
Segmentation Mask Guided End-to-End Person Search
Dingyuan Zheng, Jimin Xiao, Kaizhu Huang +1
Person search aims to search for a target person among multiple images recorded by multiple surveillance cameras, which faces various challenges from both pedestrian detection and…
Generative Adversarial Classifier for Handwriting Characters Super-Resolution
Zhuang Qian, Kaizhu Huang, Qiufeng Wang +2
Generative Adversarial Networks (GAN) receive great attentions recently due to its excellent performance in image generation, transformation, and super-resolution. However, GAN has…