Assessment of honey bee colony health using computer vision and machine learning

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DC Field	Value	Language
dc.contributor.author	Thakker, Madhav
dc.contributor.author	Anand, Saket (Advisor)
dc.contributor.author	Purandare, Swapna (Advisor)
dc.date.accessioned	2021-05-21T10:23:53Z
dc.date.available	2021-05-21T10:23:53Z
dc.date.issued	2019-11-16
dc.identifier.uri	http://repository.iiitd.edu.in/xmlui/handle/123456789/901
dc.description.abstract	The decline in biodiversity threatens food-security and the quality of life of all living beings. The decline in the number of insects (bees) is a critical phenomenon that should be looked deeply into. Computer Vision and Machine Learning techniques can be proposed as a solution to this problem. I used various techniques like Mask-RCNN, Faster-RCNN and Domain-Adaptive Faster-RCNN on the Apis Mellifera Bees (Western Honey Bee) to assess the health of honey bee colonies.	en_US
dc.language.iso	en_US	en_US
dc.publisher	IIIT-Delhi	en_US
dc.subject	Machine Learning, Computer Vision, Domain Adaptation, Regions with CNNs (RCNN)	en_US
dc.title	Assessment of honey bee colony health using computer vision and machine learning	en_US
dc.type	Other	en_US
Appears in Collections:	Year-2019

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