Results 51 to 60 of about 102,874 (306)

Comparison of CNNs and SVM for voice control wheelchair [PDF]

, 2020
In this paper, we develop an intelligent wheelchair using CNNs and SVM voice recognition methods. The data is collected from Google and some of them are self-recorded.
Mohd Ali, Azliza, Sharifuddin, Mohammad Shahrul Izham, Mohammad Shahrul Izham Sharifuddin, Sharifalillah Nordin, Azliza Mohd Ali, Nordin, Sharifalillah   +5 more
core   +1 more source

Reservoir‐Driven Neuromorphic Computing Based on Composite Rare‐Earth/Transition Metal Oxide Memristor

Advanced Functional Materials, EarlyView.
A defect‐engineered Ag/Gd2O3:Nb2O5/Pt rare earth composite oxide memristor enables stable multilevel reservoir states through pulse driven conductance modulation. Experimentally measured device responses are incorporated into a device aware reservoir computing framework for CIFAR‐100 image classification, highlighting the potential of rare earth ...
Hammad Ghazanfar, Haider Abbas, Muhammad Rabeel, Honggyun Kim, Ghulam Dastgeer, Muhammad Nasim, Furqan Zahoor, Yawar Abbas, Waqas Ahmad, Deok‐kee Kim   +9 more
wiley   +1 more source

Parameter Distribution Balanced CNNs.

, 2021
Convolutional neural network (CNN) is the primary technique that has greatly promoted the development of computer vision technologies. However, there is little research on how to allocate parameters in different convolution layers when designing CNNs. We
Wei, S, Wang, J, Zhao, Y, Liao, L, Wei, Y   +4 more
core   +1 more source

Intelligent Orthopedics: Machine Learning in Diagnosis of Bone Disease, Implants, and Bone Health Monitoring

Advanced Healthcare Materials, EarlyView.
Efficient recovery from traumatic or degenerative diseases is a great challenge, even after all the advancements in bone and cartilage regeneration. Machine learning (ML) algorithms have presented opportunities to enhance these aspects by accurately analyzing imaging data.
Maryam Kamaei, Hesam Mohammadi, Shamim Golafshan, Mojtaba Alehosseini, Mahsa Mohammadzadeh, Atefeh Golshirazi, Nasim Golafshan, Tatiane Eufrásio‐da‐Silva, Alireza Dolatshahi‐Pirouz, Gorka Orive   +9 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The automated classification of historical document scripts holds profound implications for historians, providing unprecedented insights into the contexts of ancient manuscripts.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

Daily Prediction of the Arctic Sea Ice Concentration Using Reanalysis Data Based on a Convolutional LSTM Network

Journal of Marine Science and Engineering, 2021
To meet the increasing sailing demand of the Northeast Passage of the Arctic, a daily prediction model of sea ice concentration (SIC) based on the convolutional long short-term memory network (ConvLSTM) algorithm was proposed in this study.
Quanhong Liu, Ren Zhang, Yangjun Wang, Hengqian Yan, Mei Hong   +4 more
doaj   +1 more source

Driving Scene Understanding using Spiking Neural Networks [PDF]

, 2021
One of the applications of AI lies in developing intelligent systems for safe on-road driving, other than building and perfecting self-driving vehicles, and many others.
Gaurav, Ramashish
core  

NeuroVisio SyncPatch: A Skin‐Conformal Multimodal EMG–Motion Sensing Platform for Quantitative Neuromuscular Rehabilitation and Performance Monitoring

Advanced Healthcare Materials, EarlyView.
NeuroVisio SyncPatch integrates skin‐conformal electromyography (EMG) electrodes with camera‐tracked markers to jointly assess muscle activity and three‐dimensional knee kinematics during rehabilitation. Parallel feedback pathways provide real‐time kinematic guidance during movement and post‐trial neuromuscular feedback.
Bohyung Choi, Yoo‐Jin Jun, Heewon Choee, Kun‐Do Lee, Heesoo Kim, Yu Seok Hwang, Choong Yeon Kim, Seongok Chae, Juhyun Lee, Minkyu Je, Jae‐Woong Jeong, Hyung‐Soon Park   +11 more
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

Equilibrium analysis of cellular neural networks [PDF]

, 2004
Cellular neural networks are dynamical systems, described by a large set of coupled nonlinear differential equations. The equilibrium point analysis is an important step for understanding the global dynamics and for providing design rules. We yield a set
Checco, P., CHECCO P., Biey, Mario, Gilli, Marco   +3 more
core   +1 more source