Optic disc localization in retina images using deep learning frameworks

2020 ◽  
Author(s):  
Da El Kim ◽  
Recep E. Hacisoftaoglu ◽  
Mahmut Karakaya
Keyword(s):  
Deep Learning ◽  
Optic Disc ◽  
Optic Disc Localization ◽  
Learning Frameworks ◽  
Retina Images

scholarly journals Correction to: Two-stage framework for optic disc localization and glaucoma classification in retinal fundus images using deep learning

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Muhammad Naseer Bajwa ◽  
Muhammad Imran Malik ◽  
Shoaib Ahmed Siddiqui ◽  
Andreas Dengel ◽  
Faisal Shafait ◽  
...  
Keyword(s):  
Deep Learning ◽  
Optic Disc ◽  
Fundus Images ◽  
Two Stage ◽  
Optic Disc Localization ◽  
Retinal Fundus Images ◽  
Retinal Fundus

scholarly journals Two-stage framework for optic disc localization and glaucoma classification in retinal fundus images using deep learning

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Muhammad Naseer Bajwa ◽  
Muhammad Imran Malik ◽  
Shoaib Ahmed Siddiqui ◽  
Andreas Dengel ◽  
Faisal Shafait ◽  
...  
Keyword(s):  
Deep Learning ◽  
Optic Disc ◽  
Fundus Images ◽  
Two Stage ◽  
Optic Disc Localization ◽  
Retinal Fundus Images ◽  
Retinal Fundus

Sequence-Based Deep Learning Frameworks on Enhancer-Promoter Interactions Prediction

2020 ◽  
Vol 26 ◽  
Author(s):  
Xiaoping Min ◽  
Fengqing Lu ◽  
Chunyan Li
Keyword(s):  
Gene Expression ◽  
Deep Learning ◽  
Dna Sequences ◽  
Experimental Methods ◽  
Learning Methods ◽  
Comprehensive Review ◽  
Genomic Features ◽  
Disease Mechanisms ◽  
Evaluation Strategies ◽  
Learning Frameworks

: Enhancer-promoter interactions (EPIs) in the human genome are of great significance to transcriptional regulation which tightly controls gene expression. Identification of EPIs can help us better deciphering gene regulation and understanding disease mechanisms. However, experimental methods to identify EPIs are constrained by the fund, time and manpower while computational methods using DNA sequences and genomic features are viable alternatives. Deep learning methods have shown promising prospects in classification and efforts that have been utilized to identify EPIs. In this survey, we specifically focus on sequence-based deep learning methods and conduct a comprehensive review of the literatures of them. We first briefly introduce existing sequence-based frameworks on EPIs prediction and their technique details. After that, we elaborate on the dataset, pre-processing means and evaluation strategies. Finally, we discuss the challenges these methods are confronted with and suggest several future opportunities.

scholarly journals Deep Learning-based Smart IoT Health System for Blindness Detection using Retina Images

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Amit Kumar Jaiswal ◽  
Prayag Tiwari ◽  
Sachin Kumar ◽  
Mabrook S. Al-Rakhami ◽  
Mubarak Alrashoud ◽  
...  
Keyword(s):  
Deep Learning ◽  
Health System ◽  
Retina Images

Algorithmically-consistent deep learning frameworks for structural topology optimization

2021 ◽  
Vol 106 ◽  
pp. 104483
Author(s):  
Jaydeep Rade ◽  
Aditya Balu ◽  
Ethan Herron ◽  
Jay Pathak ◽  
Rishikesh Ranade ◽  
...  
Keyword(s):  
Deep Learning ◽  
Topology Optimization ◽  
Structural Topology Optimization ◽  
Structural Topology ◽  
Learning Frameworks

Deep Learning Frameworks for COVID-19 Detection

2021 ◽  
Author(s):  
Ankit Vijayvargiya ◽  
Akshit Panchal ◽  
Abhijeet Parashar ◽  
Ayush Gautam ◽  
Jayesh Sharma ◽  
...  
Keyword(s):  
Deep Learning ◽  
Learning Frameworks
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