4.7 Article

Fully used reliable data and attention consistency for semi-supervised learning

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Computer Science, Artificial Intelligence

Attention-based label consistency for semi-supervised deep learning based image classification

Jiaming Chen et al.

Summary: This study proposes a novel attention-based label consistency (ALC) model for semi-supervised deep learning. The model effectively utilizes unlabeled data and addresses the imbalance in labeled data, demonstrating advantages on four benchmark datasets.

NEUROCOMPUTING (2021)

Article Geochemistry & Geophysics

More Diverse Means Better: Multimodal Deep Learning Meets Remote-Sensing Imagery Classification

Danfeng Hong et al.

Summary: This study introduces a general multimodal deep learning (MDL) framework for the classification and identification challenges in geoscience and remote sensing. By investigating a special case of multi-modality learning (MML), the study presents five fusion strategies and demonstrates how to train deep networks and build network architectures effectively. Experimental results on two different multimodal RS data sets confirm the efficiency and advantages of the proposed MDL framework.

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2021)

Article Geochemistry & Geophysics

Graph Convolutional Networks for Hyperspectral Image Classification

Danfeng Hong et al.

Summary: This article thoroughly investigates the applications of Convolutional Neural Networks (CNNs) and Graph Convolutional Networks (GCNs) in hyperspectral image classification. By developing a new minibatch GCN (miniGCN) to train and infer large-scale GCNs, as well as exploring fusion strategies for different types of HS features, the study achieves good classification performance.

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2021)

Article Computer Science, Artificial Intelligence

A survey on semi-supervised learning

Jesper E. Van Engelen et al.

MACHINE LEARNING (2020)

Review Computer Science, Artificial Intelligence

Graph-based semi-supervised learning: A review

Yanwen Chong et al.

NEUROCOMPUTING (2020)

Article Computer Science, Artificial Intelligence

Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning

Takeru Miyato et al.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2019)

Article Computer Science, Artificial Intelligence

An Augmented Linear Mixing Model to Address Spectral Variability for Hyperspectral Unmixing

Danfeng Hong et al.

IEEE TRANSACTIONS ON IMAGE PROCESSING (2019)

Article Computer Science, Artificial Intelligence

An easy-to-hard learning strategy for within-image co-saliency detection

Shaoyue Song et al.

NEUROCOMPUTING (2019)

Proceedings Paper Computer Science, Artificial Intelligence

Visual Attention Consistency under Image Transforms for Multi-Label Image Classification

Hao Guo et al.

2019 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2019) (2019)

Article Computer Science, Information Systems

Semi-Supervised Learning With Deep Embedded Clustering for Image Classification and Segmentation

Joseph Enguehard et al.

IEEE ACCESS (2019)

Article Computer Science, Information Systems

Unsupervised Person Re-identification: Clustering and Fine-tuning

Hehe Fan et al.

ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS (2018)

Review Computer Science, Artificial Intelligence

Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review

Waseem Rawat et al.

NEURAL COMPUTATION (2017)

Article Computer Science, Artificial Intelligence

Graph Based Constrained Semi-Supervised Learning Framework via Label Propagation over Adaptive Neighborhood

Zhao Zhang et al.

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING (2015)

Article Computer Science, Artificial Intelligence

Self-labeled techniques for semi-supervised learning: taxonomy, software and empirical study

Isaac Triguero et al.

KNOWLEDGE AND INFORMATION SYSTEMS (2015)

Article Management

Attention to Attention

William Ocasio

ORGANIZATION SCIENCE (2011)

Article

Semi-Supervised Learning (Chapelle, O. et al., Eds.; 2006) [Book reviews]

O. Chapelle et al.

IEEE TRANSACTIONS ON NEURAL NETWORKS (2009)