Results 61 to 70 of about 9,883,756 (332)

A Comparative Study of Deep Learning and Traditional Methods for Environmental Remote Sensing [PDF]

ITM Web of Conferences, 2023
Because of the accessibility of massive data from remote sensing data and developments in ML, machine learning (ML) techniques have been extensively applied in environmental remote sensing research.
Farooq Bazila, Manocha Ankush
doaj   +1 more source

Applications of Deep Learning and Reinforcement Learning to Biological Data [PDF]

, 2018
Rapid advances in hardware-based technologies during the past decades have opened up new possibilities for life scientists to gather multimodal data in various application domains, such as omics, bioimaging, medical imaging, and (brain/body)-machine ...
Amir Hussain, Hussain, Amir, Mahmud, Mufti, Kaiser, Mohammed Shamim, Vassanelli, Stefano, Hussain A., Mahmud M., Mohammed Shamim Kaiser, Kaiser M. S., Mufti Mahmud, Stefano Vassanelli, Vassanelli S., Vassanelli, S, Kaiser, MS, Hussain, A, Mahmud, M   +15 more
core   +1 more source

A Survey on Deep-Learning-Based Diabetic Retinopathy Classification [PDF]

, 2023
The number of people who suffer from diabetes in the world has been considerably increasing recently. It affects people of all ages. People who have had diabetes for a long time are affected by a condition called Diabetic Retinopathy (DR), which damages ...
Al-Maadeed, Somaya, Almaadeed, Noor, Somaya Al-Maadeed, Sebastian, Anila, Noor Almaadeed, Anila Sebastian, Omar Elharrouss, Elharrouss, Omar   +7 more
core   +1 more source

DL-GuesS: Deep Learning and Sentiment Analysis-based Cryptocurrency Price Prediction

IEEE Access, 2022
Cryptocurrencies are peer-to-peer-based transaction systems where the data exchanges are secured using the secure hash algorithm (SHA)-256 and message digest (MD)-5 algorithms.
R. Parekh, Nisarg P. Patel, Nihar Thakkar, Rajesh Gupta, Sudeep Tanwar, Gulshan Sharma, I. Davidson, Ravi Sharma   +7 more
semanticscholar   +1 more source

Deep Learning for Software Vulnerabilities Detection Using Code Metrics

IEEE Access, 2020
Software vulnerability can cause disastrous consequences for information security. Earlier detection of vulnerabilities minimizes these consequences.
Mohammed Zagane, Mustapha Kamel Abdi, Mamdouh Alenezi   +2 more
doaj   +1 more source

Deep learning encodes robust discriminative neuroimaging representations to outperform standard machine learning

Nature Communications, 2021
Recent critical commentaries unfavorably compare deep learning (DL) with standard machine learning (SML) for brain imaging data analysis. Here, the authors show that if trained following prevalent DL practices, DL methods substantially improve compared ...
Anees Abrol, Zening Fu, Mustafa Salman, Rogers Silva, Yuhui Du, Sergey Plis, Vince Calhoun   +6 more
doaj   +1 more source

Explainable deep learning for decrypting disease signatures in multiple sclerosis

, 2023
EXplainable Artificial Intelligence (XAI) recently emerged as one of the hottest topics aimed at overcoming this limitation by proposing strategies for understanding the why and the how of the outcomes of Machine (ML) and Deep Learning (DL), allowing to ...
Gloria Menegaz, Francesco Setti, Rachid Deriche, Federica Cruciani, Massimiliano Calabrese, Mauro Zucchelli, Gustavo Retuci Pinheiro, Leticia Rittner, Lorenza Brusini, Ilaria Boscolo Galazzo   +9 more
core   +1 more source

A Review on Deep Learning Methods for ECG Arrhythmia Classification

, 2020
Deep Learning (DL) has recently become a topic of study in different applications including healthcare, in which timely detection of anomalies on Electrocardiogram (ECG) can play a vital role in patient monitoring.
Loni, Mohammad,, Ghareh Baghi, Arash,, Ebrahimi, Zahra,, Daneshtalab, Masoud,   +3 more
core   +1 more source

List of Deep Learning Models

, 2020
Deep learning (DL) algorithms have recently emerged from machine learning and soft computing techniques. Since then, several deep learning (DL) algorithms have been recently introduced to scientific communities and are applied in various application ...
Amir Mosavi, Sina Faizollahzadeh Ardabili, Annamaria R. Varkonyi-Koczy   +2 more
core   +1 more source

Enhancing prediction of supraspinatus/infraspinatus tendon complex injuries through integration of deep visual features and clinical information: a multicenter two-round assessment study

Insights into Imaging, 2023
Objective Develop and evaluate an ensemble clinical machine learning–deep learning (CML-DL) model integrating deep visual features and clinical data to improve the prediction of supraspinatus/infraspinatus tendon complex (SITC) injuries. Methods Patients
Yamuhanmode Alike, Cheng Li, Jingyi Hou, Yi Long, Jinming Zhang, Chuanhai Zhou, Zongda Zhang, Qi Zhu, Tao Li, Shinan Cao, Yuanhao Zhang, Dan Wang, Shuangqin Cheng, Rui Yang   +13 more
doaj   +1 more source