Garas Gendy

Orcid: 0000-0001-6347-4826

According to our database1, Garas Gendy authored at least 15 papers between 2015 and 2023.

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Bibliography

2023
Lightweight image super-resolution based multi-order gated aggregation network.
Neural Networks, September, 2023

Lightweight image super-resolution based on deep learning: State-of-the-art and future directions.
Inf. Fusion, June, 2023


NTIRE 2023 Challenge on Stereo Image Super-Resolution: Methods and Results.
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Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

NTIRE 2023 Challenge on Efficient Super-Resolution: Methods and Results.
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Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Mixer-based Local Residual Network for Lightweight Image Super-resolution.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

A Simple Transformer-style Network for Lightweight Image Super-resolution.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
Robust Arrhythmia Classification Based on QRS Detection and a Compact 1D-CNN for Wearable ECG Devices.
IEEE J. Biomed. Health Informatics, 2022

Balanced Spatial Feature Distillation and Pyramid Attention Network for Lightweight Image Super-resolution.
Neurocomputing, 2022


Real-Time Channel Mixing Net for Mobile Image Super-Resolution.
Proceedings of the Computer Vision - ECCV 2022 Workshops, 2022

2018
A Hard C-Means Clustering Algorithm Incorporating Membership KL Divergence and Local Data Information for Noisy Image Segmentation.
Int. J. Pattern Recognit. Artif. Intell., 2018

2017
C-means clustering fuzzified by two membership relative entropy functions approach incorporating local data information for noisy image segmentation.
Signal Image Video Process., 2017

Adaptive local data and membership based KL divergence incorporating C-means algorithm for fuzzy image segmentation.
Appl. Soft Comput., 2017

2015
Fuzzy C-means algorithm incorporating local data and membership information for noisy medical image segmentation.
Proceedings of the 2015 IEEE International Conference on Electronics, 2015


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