871 citations · 3k across the 44 of their papers we have counts for
7 papers · 1 filter
DART: Domain-Adversarial Residual-Transfer Networks for Unsupervised Cross-Domain Image Classification
Xianghong Fang, Haoli Bai, Ziyi Guo +3
The accuracy of deep learning (e.g., convolutional neural networks) for an image classification task critically relies on the amount of labeled training data. Aiming to solve an im…
Robust Graph Learning from Noisy Data
Zhao Kang, Haiqi Pan, Steven C. H. Hoi +1
Learning graphs from data automatically has shown encouraging performance on clustering and semisupervised learning tasks. However, real data are often corrupted, which may cause t…
Question-Guided Hybrid Convolution for Visual Question Answering
Peng Gao, Pan Lu, Hongsheng Li +4
In this paper, we propose a novel Question-Guided Hybrid Convolution (QGHC) network for Visual Question Answering (VQA). Most state-of-the-art VQA methods fuse the high-level textu…
Adaptive Cost-sensitive Online Classification
Peilin Zhao, Yifan Zhang, Min Wu +3
Cost-Sensitive Online Classification has drawn extensive attention in recent years, where the main approach is to directly online optimize two well-known cost-sensitive metrics: (i…
Single-Shot Bidirectional Pyramid Networks for High-Quality Object Detection
Xiongwei Wu, Daoxin Zhang, Jianke Zhu +1
Recent years have witnessed many exciting achievements for object detection using deep learning techniques. Despite achieving significant progresses, most existing detectors are de…
URLNet: Learning a URL Representation with Deep Learning for Malicious URL Detection
Hung Le, Quang Pham, Doyen Sahoo +1
Malicious URLs host unsolicited content and are used to perpetrate cybercrimes. It is imperative to detect them in a timely manner. Traditionally, this is done through the usage of…