Results 41 to 50 of about 173,502 (284)

Video‐based action recognition using spurious‐3D residual attention networks

IET Image Processing, 2022
Recently, 3D Convolutional Neural Networks (3D CNNs) have attracted extensive attention in extracting spatial and temporal features in videos for their efficient feature extraction ability.
Bo Chen, Hongying Tang, Zebin Zhang, Guanjun Tong, Baoqing Li   +4 more
doaj   +1 more source

Transfer of Learning in the Convolutional Neural Networks on Classifying Geometric Shapes Based on Local or Global Invariants

Frontiers in Computational Neuroscience, 2021
The convolutional neural networks (CNNs) are a powerful tool of image classification that has been widely adopted in applications of automated scene segmentation and identification. However, the mechanisms underlying CNN image classification remain to be
Yufeng Zheng, Jun Huang, Tianwen Chen, Yang Ou, Wu Zhou   +4 more
doaj   +1 more source

Smarter Sensors Through Machine Learning: Historical Insights and Emerging Trends across Sensor Technologies

Advanced Functional Materials, EarlyView.
This review highlights how machine learning (ML) algorithms are employed to enhance sensor performance, focusing on gas and physical sensors such as haptic and strain devices. By addressing current bottlenecks and enabling simultaneous improvement of multiple metrics, these approaches pave the way toward next‐generation, real‐world sensor applications.
Kichul Lee, Osman Gul, Yeongjae Kwon, Jaeseok Jeong, Seokjoo Cho, Jihyeon Ahn, Jehee Yu, Cheolmin Kim, Donho Lee, Hyeonseok Han, Byeongju Lee, Jungrak Choi, Ji‐Hwan Ha, Yongrok Jeong, Kyungnam Kang, Ali Javey, Junseong Ahn, Inkyu Park   +17 more
wiley   +1 more source

Revolutionizing Historical Manuscript Analysis: A Deep Learning Approach with Intelligent Feature Extraction for Script Classification

Acta Informatica Pragensia
The automated classification of historical document scripts holds profound implications for historians, providing unprecedented insights into the contexts of ancient manuscripts.
Merouane Boudraa, Akram Bennour, Tahar Mekhaznia, Abdulrahman Alqarafi, Rashiq Rafiq Marie, Mohammed Al-Sarem, Ayush Dogra   +6 more
doaj   +1 more source

A test case for application of convolutional neural networks to spatio-temporal climate data: Re-identifying clustered weather patterns

, 2018
Convolutional neural networks (CNNs) can potentially provide powerful tools for classifying and identifying patterns in climate and environmental data. However, because of the inherent complexities of such data, which are often spatio-temporal, chaotic ...
Chattopadhyay, Ashesh, Hassanzadeh, Pedram, Pasha, Saba   +2 more
core   +1 more source

Multi‐Scale Interface Engineering of MXenes for Multifunctional Sensory Systems

Advanced Functional Materials, EarlyView.
MXenes, as two‐dimensional transition metal carbides and nitrides, demonstrate remarkable capabilities for multifunctional sensing applications. This review systematically examines multi‐scale interface engineering approaches that enhance sensing performance, enable diverse detection functionalities, and improve system‐level compatibility in MXene ...
Jiaying Liao, Sin‐Yi Pang, Jianhua Hao
wiley   +1 more source

Performance comparison of single and ensemble CNN, LSTM and traditional ANN models for short‐term electricity load forecasting

The Journal of Engineering, 2022
The authors propose bagged and boosted convolutional neural networks (CNNs) and long short‐term memory (LSTM) networks, and compare their performance with the bagged and boosted traditional shallow artificial neural networks (ANNs) for short‐term ...
Arurun Kathirgamanathan, Afzal Patel, Ahmed S. Khwaja, Bala Venkatesh, Alagan Anpalagan   +4 more
doaj   +1 more source

Simulating CRF with CNN for CNN

, 2019
Combining CNN with CRF for modeling dependencies between pixel labels is a popular research direction. This task is far from trivial, especially if end-to-end training is desired. In this paper, we propose a novel simple approach to CNN+CRF combination.
Gorelick, Lena, Veksler, Olga
openaire   +2 more sources

Computational Modeling Meets 3D Bioprinting: Emerging Synergies in Cardiovascular Disease Modeling

Advanced Healthcare Materials, EarlyView.
Emerging advances in three‐dimensional bioprinting and computational modeling are reshaping cardiovascular (CV) research by enabling more realistic, patient‐specific tissue platforms. This review surveys cutting‐edge approaches that merge biomimetic CV constructs with computational simulations to overcome the limitations of traditional models, improve ...
Tanmay Mukherjee, Mehdi Salar Amoli, Sarah Rezapourdamanab, Lama Rita El Shammas, Martin L. Tomov, Emilio A. Mendiola, Vahid Serpooshan, Reza Avazmohammadi   +7 more
wiley   +1 more source

A Hybrid Differential Evolution Approach to Designing Deep Convolutional Neural Networks for Image Classification

, 2018
Convolutional Neural Networks (CNNs) have demonstrated their superiority in image classification, and evolutionary computation (EC) methods have recently been surging to automatically design the architectures of CNNs to save the tedious work of manually ...
A Krizhevsky, J Bruna, KV Price, Rainer Storn, TH Chan, Y LeCun, Y Lecun   +6 more
core   +1 more source