MobileNet Model for Classifying Local Birds of Bangladesh from Image Content Using Convolutional Neural Network

dc.contributor.author	Islam, Md. Romyull
dc.contributor.author	Tasnim, Nishat
dc.contributor.author	Shuvo, Shaon Bhatta
dc.date.accessioned	2021-08-19T08:59:17Z
dc.date.available	2021-08-19T08:59:17Z
dc.date.issued	2019-12-30
dc.identifier.uri	http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/6011
dc.description.abstract	To classify bird species is quite a challenging task due to complex interdependence on various factors. There have been numerous attempts at perfecting classification. The aim of our work is to classify bird species from image data with a computer vision classification system. In this paper, we put forward a MobileNet model, which gives an amazing accuracy of up to 100%. This is the first work relating to local bird species classification. The proposed model explores a systematic approach to classification. The outcomes prove the efficiency of the model.	en_US
dc.language.iso	en_US	en_US
dc.publisher	10th International Conference on Computing, Communication and Networking Technologies, ICCCNT 2019, IEEE	en_US
dc.subject	Computational modeling	en_US
dc.subject	Task analysis	en_US
dc.subject	Computer vision	en_US
dc.subject	Convolutional neural networks	en_US
dc.subject	Image classification	en_US
dc.title	MobileNet Model for Classifying Local Birds of Bangladesh from Image Content Using Convolutional Neural Network	en_US
dc.type	Article	en_US