Search Results for author:
Found 12 papers, 4 papers with code
Improving Generalization in Meta-Learning via Meta-Gradient Augmentation
The key idea is to first break the rote memories by network pruning to address memorization overfitting in the inner loop, and then the gradients of pruned sub-networks naturally form the high-quality augmentation of the meta-gradient to alleviate learner overfitting in the outer loop.
Exploring Linear Feature Disentanglement For Neural Networks
Non-linear activation functions, e. g., Sigmoid, ReLU, and Tanh, have achieved great success in neural networks (NNs).
Series Photo Selection via Multi-view Graph Learning
Series photo selection (SPS) is an important branch of the image aesthetics quality assessment, which focuses on finding the best one from a series of nearly identical photos.
A Graph Matching Perspective With Transformers on Video Instance Segmentation
Video Instance Segmentation (VIS) needs to automatically track and segment multiple objects in videos that rely on modeling the spatial-temporal interactions of the instances.
Temporal-Relational Hypergraph Tri-Attention Networks for Stock Trend Prediction
Extensive experiments on real-world data demonstrate the effectiveness of our approach.
A Survey on Natural Language Video Localization
Natural language video localization (NLVL), which aims to locate a target moment from a video that semantically corresponds to a text query, is a novel and challenging task.
Attention Model Enhanced Network for Classification of Breast Cancer Image
In this study, we propose a novel method named Attention Model Enhanced Network (AMEN), which is formulated in a multi-branch fashion with pixel-wised attention model and classification submodular.
Learning Binary Semantic Embedding for Histology Image Classification and Retrieval
With the development of medical imaging technology and machine learning, computer-assisted diagnosis which can provide impressive reference to pathologists, attracts extensive research interests.
Reinforcing Short-Length Hashing
Due to the compelling efficiency in retrieval and storage, similarity-preserving hashing has been widely applied to approximate nearest neighbor search in large-scale image retrieval.
Mutual Linear Regression-based Discrete Hashing
Label information is widely used in hashing methods because of its effectiveness of improving the precision.
Fusion Hashing: A General Framework for Self-improvement of Hashing
In this paper, in contrast to existing hashing methods, we propose a novel generalized framework called fusion hashing (FH) to improve the precision of existing hashing methods without adding new constraints or penalty terms.
Data Structures and Algorithms Multimedia
Comprehensive Feature-based Robust Video Fingerprinting Using Tensor Model
Therefore, in the present study, we mine the assistance and consensus among different features based on tensor model, and present a new comprehensive feature to fully use them in the proposed video fingerprinting framework.
