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Deep learning architectures for computer vision applications: A study

dc.contributor.authorBagi R.; Dutta T.; Gupta H.P.
dc.date.accessioned2025-05-23T11:31:21Z
dc.description.abstractDeep learning has become one of the most preferred solution for many complex problems. It shows outstanding performance in the field of computer vision to perform tasks like, image classification, object detection, and image generation. Recently, many research efforts are focused on changing the deep learning architecture for widespread application domain. In this paper, we present a comprehensive survey on the various issues and challenges faced by deep learning techniques. Furthermore, we analyze different deep learning architectures to provide the solution for the computer vision tasks along with their importance. © Springer Nature Singapore Pte Ltd. 2020.
dc.identifier.doihttps://doi.org/10.1007/978-981-15-0694-9_56
dc.identifier.urihttp://172.23.0.11:4000/handle/123456789/13223
dc.relation.ispartofseriesLecture Notes in Networks and Systems
dc.titleDeep learning architectures for computer vision applications: A study

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