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http://dspace.dtu.ac.in:8080/jspui/handle/repository/16706
Title: | PERSON RE-IDENTIFICATION USING DENSELY CONNECTED CONVOLUTIONAL NEURAL NETWORK |
Authors: | JAISWAL, SHRADHA |
Keywords: | PERSON RE-IDENTIFICATION CONVOLUTIONAL NEURAL NETWORK DEEP LEARNING DENSENETS |
Issue Date: | Jun-2019 |
Series/Report no.: | TD-4552; |
Abstract: | A successful system for person re-identification inspired by [67], a Densely Connected Convolutional Neural Networks (DenseNet) have been developed. This architecture was proposed by Huang et el. [67] (2017) for object recognition. We are using this model for exploring the network configurations and settings for getting a better solution for person re-identification tasks. We will train and test different person re-identification datasets, search for optimal settings and other factors affecting the result. In this work, we are using two different network configurations of DenseNet model i.e., DenseNet-121 and DenseNet-161 with growth rate of 32 and 48 respectively. The model is trained and tested on different RE-ID datasets which are CUHK01 [31], MARS [44], VIPeR [27] and Market1501 [29]. |
URI: | http://dspace.dtu.ac.in:8080/jspui/handle/repository/16706 |
Appears in Collections: | M.E./M.Tech. Information Technology |
Files in This Item:
File | Description | Size | Format | |
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shradha_major_project-2.pdf | 1.48 MB | Adobe PDF | View/Open |
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