An Efficient Detection of Intracranial Hematoma Using Window-Based Stacking and YOLOv5 Framework-Reference-Cited by-同舟云学术

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An Efficient Detection of Intracranial Hematoma Using Window-Based Stacking and YOLOv5 Framework

Published:2023-06-16 Issue: Volume: Page:
ISSN:
Container-title:2023 2nd International Conference on Advancements in Electrical, Electronics, Communication, Computing and Automation (ICAECA)
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Author:

V Vidhya.¹,Gudigar Anjan²,U Raghavendra²,Basak Sudipta²,Mallappa Sankalp²,Hegde Ajay³,Menon Girish⁴

Affiliation:

1. Manipal Academy of Higher Education,Computer Science and Engineering Manipal Institute of Technology,Manipal,India,576104

2. Manipal Institute of Technology Manipal Academy of Higher Education,Instrumentation and Control Engineering,Manipal,India,576104

3. Manipal Hospitals,Department of Neurosurgery,Karnataka,India

4. Manipal Academy of Higher Education,Kasturba Medical College,Department of Neurosurgery,Manipal,India,576104

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10199105/10199188/10200714.pdf?arnumber=10200714

Reference23 articles.

1. Detecting hemorrhage types and bounding box of hemorrhage by deep learning

2. Automatic identification of intracranial hemorrhage on CT/MRI image using meta architectures improved from region-based CNN;le;Advances in Intelligent Systems and Computing,2019

3. A Survey on Performance Metrics for Object-Detection Algorithms

4. Brain Hemorrhage EXtended (BHX): Bounding box extrapolation from thick to thin slice CT images;reis;PhysioNet,2020

5. Localization of mixed intracranial hemorrhages by using a ghost convolution-based YOLO network

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