18 citations · 64 across the 18 of their papers we have counts for
18 papers
Deep graph convolution neural network with non-negative matrix factorization for community discovery
Shuliang Xu, Shenglan Liu, Lin Feng
Community discovery is an important task for graph mining. Owing to the nonstructure, the high dimensionality, and the sparsity of graph data, it is not easy to obtain an appropria…
Self-Supervised Deep Graph Embedding with High-Order Information Fusion for Community Discovery
Shuliang Xu, Shenglan Liu, Lin Feng
Deep graph embedding is an important approach for community discovery. Deep graph neural network with self-supervised mechanism can obtain the low-dimensional embedding vectors of…
Multimodal-Aware Weakly Supervised Metric Learning with Self-weighting Triplet Loss
Huiyuan Deng, Xiangzhu Meng, Lin Feng
In recent years, we have witnessed a surge of interests in learning a suitable distance metric from weakly supervised data. Most existing methods aim to pull all the similar sample…
Multi-view Low-rank Preserving Embedding: A Novel Method for Multi-view Representation
Xiangzhu Meng, Lin Feng, Huibing Wang
In recent years, we have witnessed a surge of interest in multi-view representation learning, which is concerned with the problem of learning representations of multi-view data. Wh…
FSD-10: A Dataset for Competitive Sports Content Analysis
Shenlan Liu, Xiang Liu, Gao Huang +6
Action recognition is an important and challenging problem in video analysis. Although the past decade has witnessed progress in action recognition with the development of deep lea…
The Similarity-Consensus Regularized Multi-view Learning for Dimension Reduction
Xiangzhu Meng, Huibing Wang, Lin Feng
During the last decades, learning a low-dimensional space with discriminative information for dimension reduction (DR) has gained a surge of interest. However, it's not accessible…
Hierarchic Neighbors Embedding
Shenglan Liu, Yang Yu, Yang Liu +3
Manifold learning now plays a very important role in machine learning and many relevant applications. Although its superior performance in dealing with nonlinear data distribution,…
Multi-view Locality Low-rank Embedding for Dimension Reduction
Lin Feng, Xiangzhu Meng, Huibing Wang
During the last decades, we have witnessed a surge of interests of learning a low-dimensional space with discriminative information from one single view. Even though most of them c…
A fast online cascaded regression algorithm for face alignment
Lin Feng, Caifeng Liu, Shenglan Liu +1
Traditional face alignment based on machine learning usually tracks the localizations of facial landmarks employing a static model trained offline where all of the training data is…
Bottom-up Broadcast Neural Network For Music Genre Classification
Caifeng Liu, Lin Feng, Guochao Liu +2
Music genre recognition based on visual representation has been successfully explored over the last years. Recently, there has been increasing interest in attempting convolutional…
Color Recognition for Rubik's Cube Robot
Shenglan Liu, Dong Jiang, Lin Feng +6
In this paper, we proposed three methods to solve color recognition of Rubik's cube, which includes one offline method and two online methods. Scatter balance \& extreme learning m…
Perceptual Visual Interactive Learning
Shenglan Liu, Xiang Liu, Yang Liu +4
Supervised learning methods are widely used in machine learning. However, the lack of labels in existing data limits the application of these technologies. Visual interactive learn…
Multi-view Reconstructive Preserving Embedding for Dimension Reduction
Huibing Wang, Lin Feng, Adong Kong +1
With the development of feature extraction technique, one sample always can be represented by multiple features which locate in high-dimensional space. Multiple features can re ect…
Hand Gesture Recognition with Leap Motion
Youchen Du, Shenglan Liu, Lin Feng +2
The recent introduction of depth cameras like Leap Motion Controller allows researchers to exploit the depth information to recognize hand gesture more robustly. This paper propose…
Rough extreme learning machine: a new classification method based on uncertainty measure
Lin Feng, Shuliang Xu, Feilong Wang +1
Extreme learning machine (ELM) is a new single hidden layer feedback neural network. The weights of the input layer and the biases of neurons in hidden layer are randomly generated…
Neural method for Explicit Mapping of Quasi-curvature Locally Linear Embedding in image retrieval
Shenglan Liu, Jun Wu, Lin Feng +1
This paper proposed a new explicit nonlinear dimensionality reduction using neural networks for image retrieval tasks. We first proposed a Quasi-curvature Locally Linear Embedding…
Perceptual uniform descriptor and Ranking on manifold: A bridge between image representation and ranking for image retrieval
Shenglan Liu, Jun Wu, Lin Feng +4
Incompatibility of image descriptor and ranking is always neglected in image retrieval. In this paper, manifold learning and Gestalt psychology theory are involved to solve the inc…
Three Tiers Neighborhood Graph and Multi-graph Fusion Ranking for Multi-feature Image Retrieval: A Manifold Aspect
Shenglan Liu, Muxin Sun, Lin Feng +2
Single feature is inefficient to describe content of an image, which is a shortcoming in traditional image retrieval task. We know that one image can be described by different feat…