A review of convolutional neural networks in computer vision

X Zhao, L Wang, Y Zhang, X Han, M Deveci… - Artificial Intelligence …, 2024‏ - Springer
In computer vision, a series of exemplary advances have been made in several areas
involving image classification, semantic segmentation, object detection, and image super …

A review of machine learning and deep learning for object detection, semantic segmentation, and human action recognition in machine and robotic vision

N Manakitsa, GS Maraslidis, L Moysis, GF Fragulis - Technologies, 2024‏ - mdpi.com
Machine vision, an interdisciplinary field that aims to replicate human visual perception in
computers, has experienced rapid progress and significant contributions. This paper traces …

Toward human activity recognition: a survey

G Saleem, UI Bajwa, RH Raza - Neural Computing and Applications, 2023‏ - Springer
Human activity recognition (HAR) is a complex and multifaceted problem. The research
community has reported numerous approaches to perform HAR. Along with HAR …

InstaCovNet-19: A deep learning classification model for the detection of COVID-19 patients using Chest X-ray

A Gupta, S Gupta, R Katarya - Applied Soft Computing, 2021‏ - Elsevier
Recently, the whole world became infected by the newly discovered coronavirus (COVID-
19). SARS-CoV-2, or widely known as COVID-19, has proved to be a hazardous virus …

Enhancing cervical cancer detection and robust classification through a fusion of deep learning models

SK Mathivanan, D Francis, S Srinivasan… - Scientific Reports, 2024‏ - nature.com
Cervical cancer, the second most prevalent cancer affecting women, arises from abnormal
cell growth in the cervix, a crucial anatomical structure within the uterus. The significance of …

An optimization-based diabetes prediction model using CNN and Bi-directional LSTM in real-time environment

P Madan, V Singh, V Chaudhari, Y Albagory… - Applied Sciences, 2022‏ - mdpi.com
Featured Application Diabetes is a common chronic disorder defined by excessive glucose
levels in the blood. A good diagnosis of diabetes may make a person's life better; otherwise …

Patient activity recognition using radar sensors and machine learning

G Bhavanasi, L Werthen-Brabants, T Dhaene… - Neural Computing and …, 2022‏ - Springer
Indoor human activity recognition is actively studied as part of creating various intelligent
systems with applications in smart home and office, smart health, internet of things, etc …

Motion stimulation for compositional action recognition

L Ma, Y Zheng, Z Zhang, Y Yao… - IEEE Transactions on …, 2022‏ - ieeexplore.ieee.org
Recognizing the unseen combinations of action and different objects, namely (zero-shot)
compositional action recognition, is extremely challenging for conventional action …

Graph2Net: Perceptually-enriched graph learning for skeleton-based action recognition

C Wu, XJ Wu, J Kittler - … transactions on circuits and systems for …, 2021‏ - ieeexplore.ieee.org
Skeleton representation has attracted a great deal of attention recently as an extremely
robust feature for human action recognition. However, its non-Euclidean structural …

Human skeleton pose and spatio-temporal feature-based activity recognition using ST-GCN

M Lovanshi, V Tiwari - Multimedia Tools and Applications, 2024‏ - Springer
Abstract Skeleton-based Human Activity Recognition has recently sparked a lot of attention
because skeleton data has proven resistant to changes in lighting, body sizes, dynamic …