Brain Tumor Detection Using YOLOv5 and Faster R-CNN-Reference-Cited by-同舟云学术

Brain Tumor Detection Using YOLOv5 and Faster R-CNN

Published:2023-05-05 Issue: Volume: Page:
ISSN:
Container-title:2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN)
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Author:

Kesana Anuhya¹,Nallola Jayanthi¹,Bootapally Rudra Teja¹,Amaraneni Sireesha²,Subba Reddy G V¹

Affiliation:

1. Gokaraju Rangaraju Institute of Engineering and Technology,Department of ECE,Hyderabad,India

2. VNR Vignana Jyothi Institute of Engineering and Technology,Department of ECE,Hyderabad,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10156870/10156895/10157773.pdf?arnumber=10157773

Reference14 articles.

1. Automatic Brain Tumor Grading from MRI Data Using Convolutional Neural Networks and Quality Assessment

2. A deep learning for brain tumor magnetic resonance imaging Images semantic segmentation using FCN;kumar;2018 4th International Conference on Computing Communication and Automation (ICCCA),0

3. Detection and classification of brain tumour in magnetic resonance imaging images;gadpayle;International Journal of Emerging Trends in Electrical and Electronics,0

4. Magnetic resonance imaging Image classification using adaboost for brain tumor type;minz;2017 IEEE 7th International Advance Computing Conference (IACC),0

5. Bones detection in the pelvic area on the basis of YOLO neural network

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1. Multi-Modal Image Fusion Techniques to Detect Brain Tumor Using YOLO Technology;2023 4th IEEE Global Conference for Advancement in Technology (GCAT);2023-10-06