A Short Survey on Real-Time Object Detection and its Challenges

Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/3531

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DC Field	Value	Language
dc.contributor.author	Sabat, Naba Krushna	-
dc.contributor.author	Pati, Umesh Chandra	-
dc.contributor.author	Das, Santos Kumar	-
dc.date.accessioned	2020-03-11T10:00:46Z	-
dc.date.available	2020-03-11T10:00:46Z	-
dc.date.issued	2020-03	-
dc.identifier.citation	International Conference on Emerging Trends and Advances in Electrical Engineering and Renewable Energy (ETAEERE-2020), KIIT, Bhubaneswar, India, 5-6 March 2020	en_US
dc.identifier.uri	http://hdl.handle.net/2080/3531	-
dc.description	Copyright of this paper is with proceedings publisher	en_US
dc.description.abstract	Object detection is an attractive research interest in recent years. It plays an significant role to understand the image in video analysis. Object detection technique has improved in computer vision when deep learning method came to the picture. From the last two decades, several algorithms have been developed and improved to detect the object in different conditions and still, it has number of challenges. The objective of this paper is to provide a short survey on object detection and its challenges not only in computer vision but also in the wireless sensor network.	en_US
dc.subject	Deep learning	en_US
dc.subject	Object detection	en_US
dc.subject	Convolution Neuron Network	en_US
dc.subject	Sensor	en_US
dc.subject	IoT	en_US
dc.title	A Short Survey on Real-Time Object Detection and its Challenges	en_US
dc.type	Article	en_US
Appears in Collections:	Conference Papers

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