Sharif Amit Kamran | DeepAI

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Featured Co-authors

Xingjun Ma
52 publications
Alireza Tavakkoli
20 publications
Lei Pan
20 publications
Khondker Fariha Hossain
11 publications
Ahmed Imtiaz Humayun
9 publications
Shamik Sengupta
8 publications
Stewart Lee Zuckerbrod
7 publications
George Bebis
5 publications
Tahsin Reasat
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Manash Kumar Mandal
5 publications
Fuad Rahman
4 publications

∙ 08/11/2023

Revolutionizing Space Health (Swin-FSR): Advancing Super-Resolution of Fundus Images for SANS Visual Assessment Technology

The rapid accessibility of portable and affordable retinal imaging devic...

0 Khondker Fariha Hossain, et al. ∙

∙ 03/16/2023

SwinVFTR: A Novel Volumetric Feature-learning Transformer for 3D OCT Fluid Segmentation

Accurately segmenting fluid in 3D volumetric optical coherence tomograph...

0 Sharif Amit Kamran, et al. ∙

∙ 11/16/2022

SWIN-SFTNet : Spatial Feature Expansion and Aggregation using Swin Transformer For Whole Breast micro-mass segmentation

Incorporating various mass shapes and sizes in training deep learning ar...

0 Sharif Amit Kamran, et al. ∙

∙ 06/24/2022

Feature Representation Learning for Robust Retinal Disease Detection from Optical Coherence Tomography Images

Ophthalmic images may contain identical-looking pathologies that can cau...

0 Sharif Amit Kamran, et al. ∙

∙ 10/17/2021

ECG-ATK-GAN: Robustness against Adversarial Attacks on ECG using Conditional Generative Adversarial Networks

Recently deep learning has reached human-level performance in classifyin...

0 Khondker Fariha Hossain, et al. ∙

∙ 08/04/2021

Semi-supervised Conditional GAN for Simultaneous Generation and Detection of Phishing URLs: A Game theoretic Perspective

Spear Phishing is a type of cyber-attack where the attacker sends hyperl...

0 Sharif Amit Kamran, et al. ∙

∙ 07/16/2021

ECG-Adv-GAN: Detecting ECG Adversarial Examples with Conditional Generative Adversarial Networks

Electrocardiogram (ECG) acquisition requires an automated system and ana...

11 Khondker Fariha Hossain, et al. ∙

∙ 04/14/2021

VTGAN: Semi-supervised Retinal Image Synthesis and Disease Prediction using Vision Transformers

In Fluorescein Angiography (FA), an exogenous dye is injected in the blo...

0 Sharif Amit Kamran, et al. ∙

∙ 01/03/2021

RV-GAN : Retinal Vessel Segmentation from Fundus Images using Multi-scale Generative Adversarial Networks

Retinal vessel segmentation contributes significantly to the domain of r...

34 Sharif Amit Kamran, et al. ∙

∙ 07/17/2020

Attention2AngioGAN: Synthesizing Fluorescein Angiography from Retinal Fundus Images using Generative Adversarial Networks

Fluorescein Angiography (FA) is a technique that employs the designated ...

0 Sharif Amit Kamran, et al. ∙

∙ 05/16/2020

Improving Robustness using Joint Attention Network For Detecting Retinal Degeneration From Optical Coherence Tomography Images

Noisy data and the similarity in the ocular appearances caused by differ...

0 Sharif Amit Kamran, et al. ∙

∙ 05/11/2020

Fundus2Angio: A Novel Conditional GAN Architecture for Generating Fluorescein Angiography Images from Retinal Fundus Photography

Carrying out clinical diagnosis of retinal vascular degeneration using F...

0 Sharif Amit Kamran, et al. ∙

∙ 10/13/2019

Optic-Net: A Novel Convolutional Neural Network for Diagnosis of Retinal Diseases from Optical Tomography Images

Diagnosing different retinal diseases from Spectral Domain Optical Coher...

57 Sharif Amit Kamran, et al. ∙

∙ 10/10/2018

AI Learns to Recognize Bengali Handwritten Digits: Bengali.AI Computer Vision Challenge 2018

Solving problems with Artificial intelligence in a competitive manner ha...

0 Sharif Amit Kamran, et al. ∙

∙ 08/30/2018

Total Recall: Understanding Traffic Signs using Deep Hierarchical Convolutional Neural Networks

Recognizing Traffic Signs using intelligent systems can drastically redu...

0 Sourajit Saha, et al. ∙

∙ 07/26/2017

Efficient Yet Deep Convolutional Neural Networks for Semantic Segmentation

Semantic Segmentation using deep convolutional neural network pose more ...

0 Sharif Amit Kamran, et al. ∙

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