Multi-scale YOLACT for instance segmentation

Jiexian Zeng; Huan Ouyang; Min Liu; Lu Leng; Xiang Fu

doi:10.1016/j.jksuci.2022.09.019

ScienceGate Book Chapters

JOURNAL ARTICLE

Multi-scale YOLACT for instance segmentation

Jiexian Zeng Huan Ouyang Min Liu Lu Leng Xiang Fu

Year: 2022 Journal: Journal of King Saud University - Computer and Information Sciences Vol: 34 (10)Pages: 9419-9427 Publisher: Elsevier BV

DOI: 10.1016/j.jksuci.2022.09.019

Get Full-Text PDF Get Analytical Report

Keywords:

Segmentation Artificial intelligence Computer science Pyramid (geometry) Scale-space segmentation Benchmark (surveying) Feature (linguistics) Segmentation-based object categorization Computer vision Pattern recognition (psychology) Residual Image segmentation Mathematics Algorithm

Metrics

Cited By

2.35

FWCI (Field Weighted Citation Impact)

Refs

0.88

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

Medical Image Segmentation Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Image and Object Detection Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Multi-scale YOLACT for instance segmentation

Metrics

Citation History

Topics

Related Documents

Instance Segmentation Based on Improved YOLACT

YOLACT++ Better Real-Time Instance Segmentation

Adversarial attacks on YOLACT instance segmentation

Large scale instance segmentation of outdoor environment based on improved YOLACT

Architecture Heritage Recognition Using YOLACT Instance Segmentation