PugNet: A CNN Architecture to predict the Gender and Age of Blackbuck using Pugmarks-Reference-Cited by-同舟云学术

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PugNet: A CNN Architecture to predict the Gender and Age of Blackbuck using Pugmarks

Published:2023-05-05 Issue: Volume: Page:
ISSN:
Container-title:2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT)
language:
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Author:

Saini Shubham¹,Shukla Saurabh¹,Rana Prashant Singh²,Kohli Guneet²,Singh Jaskaran³,Singh Gaurav Kumar⁴

Affiliation:

1. Lovely Professional University,Department of Forensic Science,Phagwara,Punjab,India

2. Thapar Institute of Engineering and Technology,Department of Computer Science and Engineering,Patiala,Punjab,India

3. Geeta University,Department of Forensic Science,Panipat,Haryana,India

4. Chandigarh University,Department of Forensic Science,Mohali,Punjab,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10141668/10141583/10141805.pdf?arnumber=10141805

Reference18 articles.

1. Optical coherence tomography image based eye disease detection using deep convolutional neural network

2. Identifying endangered species from footprints

3. Towards automatic wild animal monitoring: Identification of animal species in camera-trap images using very deep convolutional neural networks;villa;Ecologicalinformatics,2017

4. Deep convolutional neural network based species recognition for wild animal monitoring

5. Identifying white rhino (ceratotherium simum) by a footprint identification technique, at the individual and species levels;alibhai;EndangeredSpecies Research,2008

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