Results 61 to 70 of about 418,704 (219)

METHOD FOR JOINT OPTIMIZATION FEEDFORWARD ARTIFICIAL NEURAL NETWORKS WEIGHTS AND STRUCTURE IN DEEP MULTI-AGENT REINFORCEMENT LEARNING

Современная наука и инновации, 2022
Increasing the intelligence of tasks solved using mobile cyber-physical systems (MCPS) requires the use of artificial neural networks (ANNs) and methods of multi-agent deep reinforcement learning (MDRL).
V. I. Petrenko
doaj   +1 more source

Toward Scalable, Efficient, and Accurate Deep Spiking Neural Networks With Backward Residual Connections, Stochastic Softmax, and Hybridization

Frontiers in Neuroscience, 2020
Spiking Neural Networks (SNNs) may offer an energy-efficient alternative for implementing deep learning applications. In recent years, there have been several proposals focused on supervised (conversion, spike-based gradient descent) and unsupervised ...
Priyadarshini Panda, Sai Aparna Aketi, Kaushik Roy   +2 more
doaj   +1 more source

A Biologically Plausible Learning Rule for Deep Learning in the Brain [PDF]

, 2018
Researchers have proposed that deep learning, which is providing important progress in a wide range of high complexity tasks, might inspire new insights into learning in the brain. However, the methods used for deep learning by artificial neural networks
Bohté, Sander, Pozzi, Isabella, Roelfsema, Pieter   +2 more
core   +2 more sources

Artificial Neural Networks and Deep Learning

, 2019
An introduction on Aritifical Neural Networks and Deep Learning: * Multilayer Perceptrons * Convolutional Neural Networks (CNN)
openaire   +1 more source

Providing a Foresight Model for Selecting the Appropriate Breast Cancer Diagnosis Model [PDF]

مجله انفورماتیک سلامت و زیست پزشکی
Introduction: Selecting an appropriate model for breast cancer diagnosis is critical. Unsuitable models can compromise diagnostic accuracy, lead to incorrect outcomes, and impact clinical decision-making.
Abdolhossein Shakibaeinia, Mohsen Chagin, Amin Golabpour, Ahmad Khosravi   +3 more
doaj  

Artificial intelligence in industrial heat exchanger fouling prediction: A 20-year systematic review of AI, ML, and DL approaches

ICT Express
Fouling in heat exchangers (HXs) affects various industries by lowering efficiency and increasing costs. Traditional fouling-prediction models often do not reflect important mechanistic information and thus become very complex and less reliable.
Abdul Wahid Soomro, Miss Laiha Mat Kiah, Rafidah Md Noor, Salim Newaz Kazi, Kaleemullah Shaikh, Wajahat Ahmed Khan, Ihsan Ali   +6 more
doaj   +1 more source

Inside the “brain” of an artificial neural network: an interpretable deep learning approach to paroxysmal atrial fibrillation diagnosis from electrocardiogram signals during sinus rhythm [PDF]

, 2022
Panteleimon Pantelidis, Evangelos Oikonomou, Stamatios Lampsas, Nektarios Souvaliotis, Μichael Spartalis, Manolis Vavuranakis, Maria Bampa, Panagiotis Papapetrou, Gerasimos Siasos, Manolis Vavuranakis   +9 more
openalex   +1 more source

A CRITICAL REVIEW OF DEEP LEARNING APPLICATIONS, CHALLENGES, AND FUTURE DIRECTIONS IN STRUCTURAL ENGINEERING

International Journal for Computational Civil and Structural Engineering
Deep learning (DL), a major part of artificial intelligence (AI) is considered as a transformational technology in different areas of science, such as structural engineering.
Manaf Raid Salman, Marwan Al-Shaikhli, Hasan Ali Abbas, Hussain Hamed Ahmad, Sakhiah Abdul Kudus   +4 more
doaj   +1 more source

Research Based on Stock Predicting Model of Neural Networks Ensemble Learning

MATEC Web of Conferences, 2018
Financial time series is always one of the focus of financial market analysis and research. In recent years, with the rapid development of artificial intelligence, machine learning and financial market are more and more closely linked.
Xie Qi, Cheng Gengguo, Xu Xu, Zhao Zixuan   +3 more
doaj   +1 more source

DEEP AND MACHINE LEARNING MODELS FOR RECOGNIZING STATIC AND DYNAMIC GESTURES OF THE KAZAKH ALPHABET

Scientific Journal of Astana IT University
Currently, an increasing amount of research is directed towards solving tasks using computer vision libraries and artificial intelligence tools. Most common are the solutions and approaches utilizing machine and deep learning models of artificial neural ...
Samat Mukhanov, Raissa Uskenbayeva, Abdul Ahmad Rakhim, Im Cho Young, Aknur Yemberdiyeva, Zhansaya Bekaulova   +5 more
doaj   +1 more source