Semantic segmentation using Vision Transformers: A survey

Hans Thisanke; Chamli Deshan; Kavindu Chamith; Sachith Seneviratne; Rajith Vidanaarachchi; Damayanthi Herath

doi:10.1016/j.engappai.2023.106669

ScienceGate Book Chapters

JOURNAL ARTICLE

Semantic segmentation using Vision Transformers: A survey

Hans Thisanke Chamli Deshan Kavindu Chamith Sachith Seneviratne Rajith Vidanaarachchi Damayanthi Herath

Year: 2023 Journal: Engineering Applications of Artificial Intelligence Vol: 126 Pages: 106669-106669 Publisher: Elsevier BV

DOI: 10.1016/j.engappai.2023.106669

Get Full-Text PDF Get Analytical Report

Keywords:

Computer science Segmentation Convolutional neural network Benchmarking Artificial intelligence Image segmentation Segmentation-based object categorization Transformer Machine learning Scale-space segmentation Computer vision Pattern recognition (psychology)

Metrics

191

Cited By

34.76

FWCI (Field Weighted Citation Impact)

Refs

1.00

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Advanced Neural Network Applications

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

COVID-19 diagnosis using AI

Health Sciences → Medicine → Radiology, Nuclear Medicine and Imaging

Domain Adaptation and Few-Shot Learning

Physical Sciences → Computer Science → Artificial Intelligence

Semantic segmentation using Vision Transformers: A survey

Metrics

Citation History

Topics

Related Documents

Deep Semantic Segmentation of Echocardiographic Images using Vision Transformers

Self-supervised vision transformers for semantic segmentation

Multimodal Semantic Segmentation Based On Improved Vision Transformers

Training Vision Transformers for Semi-Supervised Semantic Segmentation

Vision Transformers: From Semantic Segmentation to Dense Prediction