JOURNAL ARTICLE

Analysis of Instance Segmentation using Mask-RCNN

Abstract

Object detection has been one of the greatest achievement in the field of Machine learning. Most of the models in the domain carry out the process of identifying the character or object using a bounding box. In the recent years, detection of the object using Instance segmentation has been in limelight. However, no interest has been showed towards the data present in the field of Entertainment. The focus of this paper is to carry out pixel level comparison and to study the behaviour of the model by analysing the result obtained at various different instances.

Keywords:
Computer science Segmentation Artificial intelligence Minimum bounding box Focus (optics) Process (computing) Carry (investment) Object (grammar) Field (mathematics) Computer vision Domain (mathematical analysis) Pixel Image segmentation Object detection Character (mathematics) Bounding overwatch Pattern recognition (psychology) Image (mathematics) Mathematics

Metrics

10
Cited By
0.43
FWCI (Field Weighted Citation Impact)
7
Refs
0.67
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
Vehicle License Plate Recognition
Physical Sciences →  Engineering →  Media Technology
Advanced Image and Video Retrieval Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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