Visual HOG-Enabled Deep ResiNet for Crime Scene Object Detection-Reference-Cited by-同舟云学术

Visual HOG-Enabled Deep ResiNet for Crime Scene Object Detection

Published:2023 Issue: Volume: Page:233-244
ISSN:2524-7565
Container-title:Algorithms for Intelligent Systems
language:
Short-container-title:

Author:

Nandhini T. J.^ORCID,Thinakaran K.^ORCID

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-99-4626-6_19

Reference20 articles.

1. Farhood H, Saberi M, Najafi M (2021) Improving object recognition in crime scenes via local interpretable model-agnostic explanations. In: 2021 IEEE 25th international enterprise distributed object computing workshop (EDOCW), 2021, pp 90–94. https://doi.org/10.1109/EDOCW52865.2021.00037

2. Proceedings of the 2019 Federated conference on computer science and information systems, Ganzha M, Maciaszek L, Paprzycki M (eds). ACSIS, vol 18, pp 391–396 (2019)

3. Sun H, Meng Z, Tao PY, Ang MH (2018) Scene recognition and object detection in a unified convolutional neural network on a mobile manipulator. In: 2018 IEEE International conference on robotics and automation (ICRA), 2018, pp 5875–5881. https://doi.org/10.1109/ICRA.2018.8460535

4. Saikia S, Fidalgo E, Alegre E, Fernández-Robles L (2017) Object detection for crime scene evidence analysis using deep learning. Image Anal Process—ICIAP 2017:14–24

5. Espinace P, Kollar T, Soto A, Roy N (2010) Indoor scene recognition through object detection. In: 2010 IEEE international conference on robotics and automation, 2010, pp 1406–1413. https://doi.org/10.1109/ROBOT.2010.5509682

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