Improving Accuracy in Object Detection Using Region-Based Convolutional Neural Network-Reference-Cited by-同舟云学术

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Improving Accuracy in Object Detection Using Region-Based Convolutional Neural Network

Published:2023-10-20 Issue: Volume: Page:1-6
ISSN:
Container-title:2023 International Conference on Evolutionary Algorithms and Soft Computing Techniques (EASCT)
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Author:

Kumar T.M Kiran¹,Aluvala Srinivas²,Mandal Preetam³,Saranya K.⁴,B Karunakara Rai⁵

Affiliation:

1. Siddaganga Institute of Technology,Department of Computer Science & Engineering,Tumkur,India

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

3. Siddhartha Institute of Technology and Sciences,Department of ECE,Hyderabad,India

4. Sona College of Technology,Department of ECE,Salem,India

5. Nitte Meenakshi Institute of Technology,Department of Electronics and Communication Engineering,Bengaluru,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10391855/10391862/10392806.pdf?arnumber=10392806

Reference14 articles.

1. A robust multiclass 3D object recognition based on modern YOLO deep learning algorithms

2. Multi-Object Detection in Security Screening Scene Based on Convolutional Neural Network

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

4. A novel real-time multiple objects detection and tracking framework for different challenges

5. Monte carlo dropblock for modelling uncertainty in object detection;Deepshikha,2021

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