Deep neural network concepts for classification using convolutional neural network: A systematic review and evaluation
In recent years, artificial intelligence (AI) has piqued the curiosity of researchers.
Convolutional Neural Networks (CNN) is a deep learning (DL) approach commonly utilized …
Convolutional Neural Networks (CNN) is a deep learning (DL) approach commonly utilized …
Fuzzy approach to computational classification of burnout—Preliminary findings
P Prokopowicz, D Mikołajewski - Applied Sciences, 2022 - mdpi.com
Featured Application Potential application of the work concerns automatic or semi-automatic
systems for early work-related stress or burnout detection and classification. Abstract There …
systems for early work-related stress or burnout detection and classification. Abstract There …
Marking attendance using modern face recognition (fr): Deep learning using the opencv method
Face Recognition and Detection encompasses an ocean of study and development
involving picture analysis and algorithm-based comprehension, sometimes known as …
involving picture analysis and algorithm-based comprehension, sometimes known as …
Deep learning based on small sample dataset: prediction of dielectric properties of SrTiO3-type perovskite with doping modification
Q Luo, H Hao, H Liu - Royal Society Open Science, 2024 - royalsocietypublishing.org
The perovskite crystal structure represents a semiconductor material poised for widespread
application, underpinned by attributes encompassing heightened efficiency, cost …
application, underpinned by attributes encompassing heightened efficiency, cost …
Convolutional Neural Network-Based Classification of Steady-State Visually Evoked Potentials with Limited Training Data
One approach employed in brain–computer interfaces (BCIs) involves the use of steady-
state visual evoked potentials (SSVEPs). This article examines the capability of artificial …
state visual evoked potentials (SSVEPs). This article examines the capability of artificial …
An approach to detect and predict epileptic seizures with high accuracy using convolutional neural networks and single-lead-ECG signal
M Ghaempour, K Hassanli, E Abiri - Biomedical Physics & …, 2024 - iopscience.iop.org
One of the epileptic patients' challenges is to detect the time of seizures and the possibility of
predicting. This research aims to provide an algorithm based on deep learning to detect and …
predicting. This research aims to provide an algorithm based on deep learning to detect and …
[PDF][PDF] Computational intelligence in engineering practice
S Osowski, B Sawicki, A Cichocki - Bulletin of the Polish Academy of …, 2021 - psjd.icm.edu.pl
2 Military University of Technology, ul. gen. Sylwestra Kaliskiego 2, 00-908 Warsaw, Poland
3 RIKEN Center for Brain Science, 2-1 Hirosawa, Wako, Saitama 351-0106, Japan discrete …
3 RIKEN Center for Brain Science, 2-1 Hirosawa, Wako, Saitama 351-0106, Japan discrete …
EpCare: Prototipe Sistem Detektor Pre-Iktal Pasien Epilepsi Berbasis Fitur CSI dari Sinyal EKG 1 Kanal Menggunakan AD8232
DP Wulandari, A Kurniawan, A Nathanael… - … Informasi dan Ilmu …, 2023 - jtiik.ub.ac.id
Kejang epilepsi dapat terjadi di sembarang waktu dan tempat, dan dalam kondisi tertentu
dapat menyebabkan cedera fatal. Oleh karena itu, kebutuhan akan perangkat wearable …
dapat menyebabkan cedera fatal. Oleh karena itu, kebutuhan akan perangkat wearable …