research
∙
08/22/2023
LCCo: Lending CLIP to Co-Segmentation
This paper studies co-segmenting the common semantic object in a set of ...
share
research
∙
04/12/2022
RL-CoSeg : A Novel Image Co-Segmentation Algorithm with Deep Reinforcement Learning
This paper proposes an automatic image co-segmentation algorithm based o...
research
∙
11/20/2021
Generating meta-learning tasks to evolve parametric loss for classification learning
The field of meta-learning has seen a dramatic rise in interest in recen...
research
∙
10/11/2021
Mining the Weights Knowledge for Optimizing Neural Network Structures
Knowledge embedded in the weights of the artificial neural network can b...
research
∙
09/21/2021
A Novel Structured Natural Gradient Descent for Deep Learning
Natural gradient descent (NGD) provided deep insights and powerful tools...
research
∙
08/17/2021
A Dense Siamese U-Net trained with Edge Enhanced 3D IOU Loss for Image Co-segmentation
Image co-segmentation has attracted a lot of attentions in computer visi...
research
∙
03/26/2021
Explore the Knowledge contained in Network Weights to Obtain Sparse Neural Networks
Sparse neural networks are important for achieving better generalization...
research
∙
03/19/2021
Improving Image co-segmentation via Deep Metric Learning
Deep Metric Learning (DML) is helpful in computer vision tasks. In this ...
research
∙
03/15/2021
Evolving parametrized Loss for Image Classification Learning on Small Datasets
This paper proposes a meta-learning approach to evolving a parametrized ...
research
∙
03/10/2021
Fusing Medical Image Features and Clinical Features with Deep Learning for Computer-Aided Diagnosis
Current Computer-Aided Diagnosis (CAD) methods mainly depend on medical ...
research
∙
07/27/2020
Contraction Mapping of Feature Norms for Classifier Learning on the Data with Different Quality
The popular softmax loss and its recent extensions have achieved great s...
research
∙
05/11/2020
A New Computer-Aided Diagnosis System with Modified Genetic Feature Selection for BI-RADS Classification of Breast Masses in Mammograms
Mammography remains the most prevalent imaging tool for early breast can...
research
∙
11/18/2019
Automatic Image Co-Segmentation: A Survey
Image co-segmentation is important for its advantage of alleviating the ...
research
∙
10/17/2019
