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Review on Applications of Object Detection using Deep Learning

Human cerebral mantle not requires a second to separate the area of thing inside the image similarly as recall it when it ensures; in spite of that, machine requires a time and large amount of data to perform a similar task. Deep neural network dependent on convolution neural network allows high acc...

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Bibliographic Details
Published in:International journal for research in applied science and engineering technology 2022-05, Vol.10 (5), p.3686-3688
Main Authors: Mali, Mohan Kashinath, Chavan, Vijaya Sayaji
Format: Article
Language:English
Online Access:Get full text
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Summary:Human cerebral mantle not requires a second to separate the area of thing inside the image similarly as recall it when it ensures; in spite of that, machine requires a time and large amount of data to perform a similar task. Deep neural network dependent on convolution neural network allows high accuracy and better results in object discovery .To develop deep neural networks, large amount of information such as images, video recordings are required and also it requires large amount of time. As computational cost of PC vision is incredibly high, highly learning methodology, where a model ready on one endeavor is reused on one more associated task, gives improved results. Through the survey and investigation of deep learning-based article recognition techniques recently, this work integrates the going with parts: spine interconnection, setback limits and planning procedures, customary thing distinguishing proof plans, multi-layered issues, the datasets and appraisal aspects, applications, and future headway headings. We belief this overview paper will be helpful for experts in the field of object detection. Keywords: Artificial Intelligence, Deep Learning, Neural Network, Object Detection
ISSN:2321-9653
2321-9653
DOI:10.22214/ijraset.2022.43075