Research Article
Human Body Part Detection and External Injury Prediction Using Convolutional Neural Network
@INPROCEEDINGS{10.4108/eai.16-5-2020.2303952, author={Aliasgar Haji and Riya Saraf and Dipti Pawade and Ashwini Dalvi and Irfan Siddavatam}, title={Human Body Part Detection and External Injury Prediction Using Convolutional Neural Network}, proceedings={Proceedings of the First International Conference on Advanced Scientific Innovation in Science, Engineering and Technology, ICASISET 2020, 16-17 May 2020, Chennai, India}, publisher={EAI}, proceedings_a={ICASISET}, year={2021}, month={1}, keywords={body part detection injury detection convolutional neural network (cnn)}, doi={10.4108/eai.16-5-2020.2303952} }- Aliasgar Haji
Riya Saraf
Dipti Pawade
Ashwini Dalvi
Irfan Siddavatam
Year: 2021
Human Body Part Detection and External Injury Prediction Using Convolutional Neural Network
ICASISET
EAI
DOI: 10.4108/eai.16-5-2020.2303952
Abstract
Fake callers continue to disrupt emergency ambulance services in the state with its call center registering 7 percent fake calls every day on an average. This is a growing problem and it needs to be curbed at the earliest as it not only wastes the time of the operators but also keeps the line busy hence causing a delay in emergency services which may even result in the death of the victim. Hence, we propose a solution to validate whether the request for ambulance services is genuine or not. The main aim is to detect and identity from an image whether a human body part is present or not. Even if the image does not contain the entire human in any particular pose and only a part of his/her body is present. We also detect any visible external injury on the body part. This would be a proof of concept in the form of a machine learning model that can successfully detect feet, face, hands and any external injury present in the image provided to it.