Human Body Part Detection and External Injury Prediction Using Convolutional Neural Network

Haji, Aliasgar and Saraf, Riya and Pawade, Dipti and Dalvi, Ashwini and Siddavatam, Irfan (2021) Human Body Part Detection and External Injury Prediction Using Convolutional Neural Network. In: ICASISET 2020, 16-17 May 2020, Chennai, India.

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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.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: body part detection injury detection convolutional neural network (cnn)
Subjects: Q Science > QA Mathematics > QA76 Computer software
Depositing User: EAI Editor III.
Date Deposited: 09 Mar 2021 09:48
Last Modified: 09 Mar 2021 09:48
URI: https://eprints.eudl.eu/id/eprint/1403

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