Performance Evaluation of Semantic Segmentation Models with and without Attention for White Blood Cells Segmentation-Reference-Cited by-同舟云学术

Performance Evaluation of Semantic Segmentation Models with and without Attention for White Blood Cells Segmentation

Published:2023-09-03 Issue: Volume: Page:
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Container-title:Proceedings of the 14th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics
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Author:

Jodha Rajshree¹^ORCID,Mishra Priyanka¹^ORCID,Arul Jothi J. Angel²^ORCID,Saifi Sameer³^ORCID,Purohit Abhishek⁴^ORCID

Affiliation:

1. Indian Institute of Information Technology Kota, Kota, Rajasthan, India

2. BITS Pilani Dubai Campus, Dubai, United Arab Emirates

3. Indian Institute of Information Technology Kota, Kota, India

4. All India Institute of Medical Sciences Jodhpur, Jodhpur, India

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3584371.3612975

Reference17 articles.

1. Microscopic Blood Smear Segmentation and Classification Using Deep Contour Aware CNN and Extreme Machine Learning

2. Recognition of Knee Osteoarthritis (KOA) Using YOLOv2 and Classification Based on Convolutional Neural Network

3. Javaria Amin , Muhammad Sharif , Muhammad Almas Anjum , Yunyoung Nam , Seifedine Kadry , and David Taniar . Diagnosis of covid-19 infection using three-dimensional semantic segmentation and classification of computed tomography images. Computers , Materials and Continua , pages 2451 -- 2467 , 2021 . Javaria Amin, Muhammad Sharif, Muhammad Almas Anjum, Yunyoung Nam, Seifedine Kadry, and David Taniar. Diagnosis of covid-19 infection using three-dimensional semantic segmentation and classification of computed tomography images. Computers, Materials and Continua, pages 2451--2467, 2021.

4. Texture feature based classification on microscopic blood smear for acute lymphoblastic leukemia detection

5. WBC-Net: A white blood cell segmentation network based on UNet++ and ResNet