A Rapid Object Recognition Scenario Based on Improved YOLO-V3 Network-Reference-Cited by-同舟云学术

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A Rapid Object Recognition Scenario Based on Improved YOLO-V3 Network

Published:2023-10-20 Issue: Volume: Page:1-5
ISSN:
Container-title:2023 International Conference on Evolutionary Algorithms and Soft Computing Techniques (EASCT)
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Author:

Kumar Suvarna Sunil¹,K N Shreenath²,Sunil G³,P Vishwanath⁴,Shankar Smitha Sharath⁵

Affiliation:

1. Malla Reddy Engineering College for Women,IT Department,Hyderabad,India

2. Siddaganga Institute of Technology,Department of CSE,Tumakuru,India

3. School of Computer Science & Artificial Intelligence SR University,Warangal,India

4. Sir M. Visvesvaraya College of Engineering,Electronics and Communication Engineering,Raichur,India

5. Nitte Meenakshi Institute of Technology,Department of ECE,Bengaluru,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10391855/10391862/10393004.pdf?arnumber=10393004

Reference15 articles.

1. Maximum entropy scaled super pixels segmentation for multi-object detection and scene recognition via deep belief network

2. Saliency guided faster-RCNN (SGFr-RCNN) model for object detection and recognition

3. A multimodal semantic segmentation for airport runway delineation in panchromatic remote sensing images

4. An Attention Mechanism-Improved YOLOv7 Object Detection Algorithm for Hemp Duck Count Estimation

5. DFC-D: A dynamic weight-based multiple features combination for real-time moving object detection

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