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A Machine Learning Approach to Detect Wounded Dog

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2021
Amit Lal Das, K.M. Ashikur Rahman

Amit Lal Das and K.M.Ashikur Rahman. A Machine Learning Approach to Detect Wounded Dog. International Journal of Computer Applications 183(43):1-5, December 2021. BibTeX

	author = {Amit Lal Das and K.M.Ashikur Rahman},
	title = {A Machine Learning Approach to Detect Wounded Dog},
	journal = {International Journal of Computer Applications},
	issue_date = {December 2021},
	volume = {183},
	number = {43},
	month = {Dec},
	year = {2021},
	issn = {0975-8887},
	pages = {1-5},
	numpages = {5},
	url = {},
	doi = {10.5120/ijca2021921828},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


Now, everything is automated. There are various kinds of animals around us. Some animals live with us, some have residence, some have an owner, some are in a specific area. Dogs are such kind of animal that they live with us. But many of the dogs have no owner or residence. And they cannot have a healthy life. They also get wounds in many ways but have no remedy. They live with us or around us. If they are wounded, the disease can spread by them. So we need to detect them immediately and concern the authority. So we make such kind of system which can identify a wounded dog. We use a dataset of 409 data for this purpose in yolov3.


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Yolov3, Object detection, Machine Learning, Wounds, Dog, Google colab.