5 citations · 18 across the 11 of their papers we have counts for
11 papers
AdvMask: A Sparse Adversarial Attack Based Data Augmentation Method for Image Classification
Suorong Yang, Jinqiao Li, Jian Zhao +1
Data augmentation is a widely used technique for enhancing the generalization ability of convolutional neural networks (CNNs) in image classification tasks. Occlusion is a critical…
AugRmixAT: A Data Processing and Training Method for Improving Multiple Robustness and Generalization Performance
Xiaoliang Liu, Furao Shen, Jian Zhao +1
Deep neural networks are powerful, but they also have shortcomings such as their sensitivity to adversarial examples, noise, blur, occlusion, etc. Moreover, ensuring the reliabilit…
Review Neural Networks about Image Transformation Based on IGC Learning Framework with Annotated Information
Yuanjie Yan, Suorong Yang, Yan Wang +2
Image transformation, a class of vision and graphics problems whose goal is to learn the mapping between an input image and an output image, develops rapidly in the context of deep…
SASICM A Multi-Task Benchmark For Subtext Recognition
Hua Yan, Feng Han, Junyi An +3
Subtext is a kind of deep semantics which can be acquired after one or more rounds of expression transformation. As a popular way of expressing one's intentions, it is well worth s…
Faster and Simpler Siamese Network for Single Object Tracking
Shaokui Jiang, Baile Xu, Jian Zhao +1
Single object tracking (SOT) is currently one of the most important tasks in computer vision. With the development of the deep network and the release for a series of large scale d…
IC Networks: Remodeling the Basic Unit for Convolutional Neural Networks
Junyi An, Fengshan Liu, Jian Zhao +1
Convolutional neural network (CNN) is a class of artificial neural networks widely used in computer vision tasks. Most CNNs achieve excellent performance by stacking certain types…
IC Neuron: An Efficient Unit to Construct Neural Networks
Junyi An, Fengshan Liu, Jian Zhao +1
As a popular machine learning method, neural networks can be used to solve many complex tasks. Their strong generalization ability comes from the representation ability of the basi…
Pairwise Interactive Graph Attention Network for Context-Aware Recommendation
Yahui Liu, Furao Shen, Jian Zhao
Context-aware recommender systems (CARS), which consider rich side information to improve recommendation performance, have caught more and more attention in both academia and indus…
IC-Network: Efficient Structure for Convolutional Neural Networks
Junyi An, Fengshan Liu, Jian Zhao +1
Neural networks have been widely used, and most networks achieve excellent performance by stacking certain types of basic units. Compared to increasing the depth and width of the n…
Label Mapping Neural Networks with Response Consolidation for Class Incremental Learning
Xu Zhang, Yang Yao, Baile Xu +4
Class incremental learning refers to a special multi-class classification task, in which the number of classes is not fixed but is increasing with the continual arrival of new data…
Operation-aware Neural Networks for User Response Prediction
Yi Yang, Baile Xu, Furao Shen +1
User response prediction makes a crucial contribution to the rapid development of online advertising system and recommendation system. The importance of learning feature interactio…