Results 31 to 40 of about 84,699 (302)

Driver Drowsiness Detection using Evolutionary Machine Learning: A Survey [PDF]

BIO Web of Conferences
One of the factors that kills hundreds of people every year is driving accidents caused by drowsy drivers. There are different methods to prevent this type of accidents. Recently Machine Learning (ML) and Deep Learning (DL) have emerged as very effective
Yasir Jumhaa Maha, Majeed Osama, Taima Alaa   +2 more
doaj   +1 more source

Ensemble Learning, Deep Learning-Based and Molecular Descriptor-Based Quantitative Structure–Activity Relationships

Molecules, 2023
A deep learning-based quantitative structure–activity relationship analysis, namely the molecular image-based DeepSNAP–deep learning method, can successfully and automatically capture the spatial and temporal features in an image generated from a three ...
Yasunari Matsuzaka, Yoshihiro Uesawa
doaj   +1 more source

Are Deep Learning Approaches Suitable for Natural Language Processing? [PDF]

, 2016
In recent years, Deep Learning (DL) techniques have gained much at-tention from Artificial Intelligence (AI) and Natural Language Processing (NLP) research communities because these approaches can often learn features from data without the need for human
Alshahrani, S., S. Alshahrani, E. Kapetanios, Kapetanios, E.   +3 more
core   +1 more source

Spatial modelling of soil salinity: deep or shallow learning models?

, 2021
Understanding the spatial distribution of soil salinity is required to conserve land against degradation and desertification. Against this background, this study is the first attempt to predict soil salinity in the Jaghin basin, in southern Iran, by ...
Mohammadifar, A., Collins, A. L., Golzari, S., Gholami, H.   +3 more
core   +1 more source

Applications of deep learning techniques for automated multiple sclerosis detection using magnetic resonance imaging: A review [PDF]

, 2021
Multiple Sclerosis (MS) is a type of brain disease which causes visual, sensory, and motor problems for people with a detrimental effect on the functioning of the nervous system.
Shoeibi, Afshin, Nahavandi, Saeid, Khodatars, Marjane, Rezaei, Mitra, Gorriz, Juan Manuel, Heras, Jónathan, Alizadehsani, Roohallah, Jafari, Mahboobeh, Panahiazar, Maryam, Moridian, Parisa, Acharya, U. Rajendra, Khozeimeh, Fahime   +11 more
core   +1 more source

Deep learning: Applications, architectures, models, tools, and frameworks: A comprehensive survey

CAAI Transactions on Intelligence Technology, 2023
Deep Learning (DL) is a subfield of machine learning that significantly impacts extracting new knowledge. By using DL, the extraction of advanced data representations and knowledge can be made possible.
Mehdi Gheisari, Fereshteh Ebrahimzadeh, Mohamadtaghi Rahimi, Mahdieh Moazzamigodarzi, Yang Liu, Pijush Kanti Dutta Pramanik, Mohammad Ali Heravi, Abolfazl Mehbodniya, Mustafa Ghaderzadeh, Mohammad Reza Feylizadeh, Saeed Kosari   +10 more
doaj   +1 more source

Deep learning methods may not outperform other machine learning methods on analyzing genomic studies

Frontiers in Genetics, 2022
Deep Learning (DL) has been broadly applied to solve big data problems in biomedical fields, which is most successful in image processing. Recently, many DL methods have been applied to analyze genomic studies. However, genomic data usually has too small
Yao Dong, Yao Dong, Yao Dong, Shaoze Zhou, Li Xing, Yumeng Chen, Yumeng Chen, Ziyu Ren, Ziyu Ren, Yongfeng Dong, Yongfeng Dong, Xuekui Zhang   +11 more
doaj   +1 more source

Deep Learning Strategies for Enhanced Molecular Docking and Virtual Screening

, 2023
Over the last few years, machine learning (ML) and deep learning (DL) have been revolutionising the computer-aided drug discovery landscape. With the recent availability of the so-called ultra-large virtual libraries (libraries with up to billions of ...
Eduardo, Krempser, Matheus, Müller Pereira da Silva, Fábio, Lima Custódio, Isabella, Alvim Guedes, Laurent, Emmanuel Dardenne   +4 more
core   +1 more source

FNMD: An Evaluation of Machine Learning and Deep Learning Techniques for Fake News Detection

, 2023
Fake news proliferation on social media platforms has become alarming because it poses threats to various aspects of society. Fake news encompasses intentionally falsified information designed to mislead readers and manipulate public perception ...
Hosseini, SM., Abdi, A., Daneshvar, B.
core   +1 more source

A Novel Technique to Support Deep Learning Applications in a Model-Based Embedded Software Design Methodology

IEEE Access, 2023
As deep learning applications are getting popular in embedded systems, how to support deep learning applications in the model-based embedded software design methodology becomes a challenging problem. A previous solution is to represent each deep learning
Jangryul Kim, Jaewoo Son, Soonhoi Ha
doaj   +1 more source