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A Strong and Efficient Baseline for Vehicle Re-Identification Using Deep Triplet Embedding Cover

A Strong and Efficient Baseline for Vehicle Re-Identification Using Deep Triplet Embedding

Journal of Artificial Intelligence and Soft Computing Research
Volume 10 (2020): Issue 1 (January 2020)
By: Ratnesh Kumar,  Edwin Weill,  Farzin Aghdasi and  Parthasarathy Sriram  
Open Access
|Dec 2019

Authors

Ratnesh Kumar

ratneshk@nvidia.com

NVIDIA

Edwin Weill

eweill@nvidia.com

NVIDIA

Farzin Aghdasi

NVIDIA

Parthasarathy Sriram

NVIDIA
DOI: https://doi.org/10.2478/jaiscr-2020-0003
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Language: English
Page range: 27 - 45
Submitted on: Sep 30, 2019
|
Accepted on: Nov 11, 2019
|
Published on: Dec 11, 2019
Published by: SAN University
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
convolutional neural networks,
re-identification,
triplet networks,
siamese networks,
embedding,
hard data mining,
contrastive loss
Related subjects:
Computer sciences,
Databases and data mining,
Artificial intelligence

© 2019 Ratnesh Kumar, Edwin Weill, Farzin Aghdasi, Parthasarathy Sriram, published by SAN University
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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