169 citations · 799 across the 43 of their papers we have counts for
9 papers · 1 filter
Quantum Tensor Network in Machine Learning: An Application to Tiny Object Classification
Fanjie Kong, Xiao-yang Liu, Ricardo Henao
Tiny object classification problem exists in many machine learning applications like medical imaging or remote sensing, where the object of interest usually occupies a small region…
Spatiotemporal Graph Neural Network based Mask Reconstruction for Video Object Segmentation
Daizong Liu, Shuangjie Xu, Xiao-Yang Liu +3
This paper addresses the task of segmenting class-agnostic objects in semi-supervised setting. Although previous detection based methods achieve relatively good performance, these…
ANIMC: A Soft Framework for Auto-weighted Noisy and Incomplete Multi-view Clustering
Xiang Fang, Yuchong Hu, Pan Zhou +1
Multi-view clustering has wide applications in many image processing scenarios. In these scenarios, original image data often contain missing instances and noises, which is ignored…
Jointly Cross- and Self-Modal Graph Attention Network for Query-Based Moment Localization
Daizong Liu, Xiaoye Qu, Xiao-Yang Liu +3
Query-based moment localization is a new task that localizes the best matched segment in an untrimmed video according to a given sentence query. In this localization task, one shou…
TGAN: Deep Tensor Generative Adversarial Nets for Large Image Generation
Zihan Ding, Xiao-Yang Liu, Miao Yin +1
Deep generative models have been successfully applied to many applications. However, existing works experience limitations when generating large images (the literature usually gene…
3D seismic data denoising using two-dimensional sparse coding scheme
Ming-Jun Su, Jingbo Chang, Feng Qian +2
Seismic data denoising is vital to geophysical applications and the transform-based function method is one of the most widely used techniques. However, it is challenging to design…
Seismic facies recognition based on prestack data using deep convolutional autoencoder
Feng Qian, Miao Yin, Ming-Jun Su +2
Prestack seismic data carries much useful information that can help us find more complex atypical reservoirs. Therefore, we are increasingly inclined to use prestack seismic data f…
Efficient Two-Dimensional Sparse Coding Using Tensor-Linear Combination
Fei Jiang, Xiao-Yang Liu, Hongtao Lu +1
Sparse coding (SC) is an automatic feature extraction and selection technique that is widely used in unsupervised learning. However, conventional SC vectorizes the input images, wh…
Graph Regularized Tensor Sparse Coding for Image Representation
Fei Jiang, Xiao-Yang Liu, Hongtao Lu +1
Sparse coding (SC) is an unsupervised learning scheme that has received an increasing amount of interests in recent years. However, conventional SC vectorizes the input images, whi…