Noha M. Ghatwary

Orcid: 0000-0002-4019-479X

Affiliations:
  • University of Lincoln, Computer Science Department, UK
  • Arab Academy for Science; Technology and Maritime Transport, Alexandria, Egypt


According to our database1, Noha M. Ghatwary authored at least 19 papers between 2014 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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In proceedings 
Article 
PhD thesis 
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Links

Online presence:

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Bibliography

2023
Why is the winner the best?
CoRR, 2023

Myositis Detection From Muscle Ultrasound Images Using a Proposed YOLO-CSE Model.
IEEE Access, 2023

Why is the Winner the Best?
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Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challenge.
CoRR, 2022

Endoscopic computer vision challenges 2.0.
Proceedings of the 4th International Workshop and Challenge on Computer Vision in Endoscopy (EndoCV 2022) co-located with the 19th IEEE International Symposium on Biomedical Imaging (ISBI 2022), 2022

Predicting Respiratory Diseases from Lung Sounds using Ensemble Model.
Proceedings of the 5th International Conference on Communications, 2022

Intelligent Assistance System for Visually Impaired/Blind People (ISVB).
Proceedings of the 5th International Conference on Communications, 2022

2021
Learning Spatiotemporal Features for Esophageal Abnormality Detection From Endoscopic Videos.
IEEE J. Biomed. Health Informatics, 2021

Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy.
Medical Image Anal., 2021

PolypGen: A multi-center polyp detection and segmentation dataset for generalisability assessment.
CoRR, 2021

2020
Automatic esophageal abnormality detection and classification.
PhD thesis, 2020

A translational pathway of deep learning methods in GastroIntestinal Endoscopy.
CoRR, 2020

Endoscopy disease detection challenge 2020.
CoRR, 2020

2019
Early esophageal adenocarcinoma detection using deep learning methods.
Int. J. Comput. Assist. Radiol. Surg., 2019

Esophageal Abnormality Detection Using DenseNet Based Faster R-CNN With Gabor Features.
IEEE Access, 2019

GFD Faster R-CNN: Gabor Fractal DenseNet Faster R-CNN for Automatic Detection of Esophageal Abnormalities in Endoscopic Images.
Proceedings of the Machine Learning in Medical Imaging - 10th International Workshop, 2019

2017
Automated Detection of Barrett's Esophagus Using Endoscopic Images: A Survey.
Proceedings of the Medical Image Understanding and Analysis - 21st Annual Conference, 2017

Automatic grade classification of Barretts Esophagus through feature enhancement.
Proceedings of the Medical Imaging 2017: Computer-Aided Diagnosis, 2017

2014
Adaptive video watermarking integrating a fuzzy wavelet-based human visual system perceptual model.
Multim. Tools Appl., 2014


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