YOLOv5-M: A Deep Neural Network for Medical Object Detection in Real-time

Author:

Bashir Saba1,Qureshi Rizwan2,Shah Abbas3,Fan Xinqi4,Alam Tanvir2

Affiliation:

1. National University of Computer and Emerging Sciences,Karachi,Pakistan

2. College of Science and Engineering, Hamad Bin Khalifa University,Doha,Qatar

3. Mehran University of Engineering and Technology,Jamshoro,Pakistan

4. City University of Hong Kong,Hong Kong

Publisher

IEEE

Reference33 articles.

1. Fast Identification of Possible Drug Treatment of Coronavirus Disease-19 (COVID-19) through Computational Drug Repurposing Study

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4. Covid-19base v3: Update of the knowledgebase for drugs and biomedical entities linked to covid-19;abdullah basit;J Public Health Frontier,2023

5. Ssd: Single shot multibox detector;liu;European Conference on Computer Vision,0

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1. Disease Detection in Abdominal CT Images Using the YOLOv5 Algorithm: A Deep Learning Approach;2024 59th International Scientific Conference on Information, Communication and Energy Systems and Technologies (ICEST);2024-07-01

2. Performance Evaluation of YOLOv5 on Edge Devices for Personal Protective Equipment Detection;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30

3. A Comprehensive Systematic Review of YOLO for Medical Object Detection (2018 to 2023);IEEE Access;2024

4. Treat Noise as Domain Shift: Noise Feature Disentanglement for Underwater Perception and Maritime Surveys in Side-Scan Sonar Images;IEEE Transactions on Geoscience and Remote Sensing;2023

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