Deep Learning Based Hand Wrist Segmentation

The international arab journal of information technology

article

GokulaKrishnan Elumalai¹  Malathi Ganesan¹ 

[1] School of Computer Science and Engineering, Vellore Institute of Technology

关键词: Hand wrist;    segmentation;    mask R-CNN;    fast R-CNN;    faster R-CNN;    object detection;   

DOI  :  10.34028/iajit/19/5/10

学科分类：计算机科学（综合）

来源: Zarqa University

【 摘 要 】

Deep learning is one of the trending technologies in computer vision to identify and classify objects. Deep learningis a subset of Machine Learning and Artificial Intelligence. Detecting and classifying the object was a challenging task intraditional computer vision techniques, and now there are numerous deep learning techniques scaled up to achieve this. Theprimary purpose of the research is to detect and segment the human hand wrist region using deep learning methods. Thisresearch is widespread to deep learning enthusiasts who needs to segment custom objects using instance segmentation. Wedemonstrated a segmented hand wrist using the Mask Regional Convolutional Neural Network (R-CNN) technique with anaverage accuracy of 99.73%. This work also compares the performance evaluation of baseline and custom Hand Wrist Mask R- CNN. The achieved validation class loss is 0.00866 training and 0.02736 validation; both the values are comparatively deficientcompared with baseline Mask R-CNN.

【 授权许可】

Unknown