Results 51 to 60 of about 695,054 (265)

Human-Assisted vs. Deep Learning Feature Extraction: An Evaluation of ECG Features Extraction Methods for Arrhythmia Classification Using Machine Learning

Applied Sciences, 2022
The success of arrhythmia classification tasks with Machine Learning (ML) algorithms is based on the handcrafting extraction of features from Electrocardiography (ECG) signals.
Larissa Montenegro, Mariana Abreu, Ana Fred, Jose M. Machado   +3 more
doaj   +1 more source

The Combined Effect of Obesity and Contraceptive Use on Pulmonary Embolism in Adolescent Females Residing in the United States

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Combined oral contraceptive (COC) use in obese adult women dramatically increases the relative risk of developing a pulmonary embolism (PE). The risk of a PE in obese adolescent females taking contraceptives is currently unknown. The purpose of this investigation was to determine the effect of body mass index (BMI) and contraceptive
John Puetz, Joanne Salas
wiley   +1 more source

Large-Scale, Multiple Level-of-Detail Change Detection from Remote Sensing Imagery Using Deep Visual Feature Clustering

Remote Sensing, 2021
In the era of big data, where massive amounts of remotely sensed imagery can be obtained from various satellites accompanied by the rapid change in the surface of the Earth, new techniques for large-scale change detection are necessary to facilitate ...
Rasha S. Gargees, Grant J. Scott
doaj   +1 more source

Deep motion features for visual tracking

2016 23rd International Conference on Pattern Recognition (ICPR), 2016
ICPR 2016.
Susanna Gladh, Martin Danelljan, Fahad Shahbaz Khan, Michael Felsberg   +3 more
openaire   +4 more sources

Deep unsupervised feature selection by discarding nuisance and correlated features

Neural Networks, 2022
Modern datasets often contain large subsets of correlated features and nuisance features, which are not or loosely related to the main underlying structures of the data. Nuisance features can be identified using the Laplacian score criterion, which evaluates the importance of a given feature via its consistency with the Graph Laplacians' leading ...
Uri Shaham 0001, Ofir Lindenbaum, Jonathan Svirsky, Yuval Kluger   +3 more
openaire   +4 more sources

Feasibility and Safety of Somato‐Cognitive Coordination Therapy for Cerebellar Ataxia Following Pediatric Brain Tumor Treatment

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Cerebellar ataxia after pediatric brain tumor treatment can cause persistent gait, balance, and speech impairment, yet no established rehabilitation strategy exists. Somato‐cognitive coordination therapy (SCCT) is a virtual reality–guided intervention designed to promote sensorimotor integration through visually constrained reaching
Masanobu Takeuchi, Takashi Matsuzawa, Jun Yamanishi, Masahiro Yoshitomi, Junji Ikeda, Shin‐Ichi Tsujimoto, Yasuteru Yamaguchi, Norio Shiba, Dhroov Pathare, Ayumi Kato, Masahiko Hara   +10 more
wiley   +1 more source

A Bayesian Scene-Prior-Based Deep Network Model for Face Verification

Sensors, 2018
Face recognition/verification has received great attention in both theory and application for the past two decades. Deep learning has been considered as a very powerful tool for improving the performance of face recognition/verification recently.
Huafeng Wang, Wenfeng Song, Wanquan Liu, Ning Song, Yuehai Wang, Haixia Pan   +5 more
doaj   +1 more source

Detection of Exceptional Malware Variants Using Deep Boosted Feature Spaces and Machine Learning

Applied Sciences, 2021
Malware is a key component of cyber-crime, and its analysis is the first line of defence against cyber-attack. This study proposes two new malware classification frameworks: Deep Feature Space-based Malware classification (DFS-MC) and Deep Boosted ...
Muhammad Asam, Shaik Javeed Hussain, Mohammed Mohatram, Saddam Hussain Khan, Tauseef Jamal, Amad Zafar, Asifullah Khan, Muhammad Umair Ali, Umme Zahoora   +8 more
doaj   +1 more source

Prevalence of 21 Physician‐Defined Severe Toxicities Following Childhood Acute Lymphoblastic Leukemia Treatment: Australian Retrospective Cohort Study

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Acute lymphoblastic leukemia (ALL) is the most common pediatric cancer, with an overall survival now surpassing 90% in developed countries. However, treatments are not without adverse effects. In this study, we apply the severe toxicity‐free survival (STFS) framework to determine the prevalence of 21 physician‐defined severe ...
Lane Collier, Brittany Grantham, Camilla Grud Nielsen, Louise Lundgren, Liv Andrés‐Jensen, Kjeld Schmiegelow, Chris Selman, Gareth Ball, Elyse Passmore, David A. Elliott, Rachel Conyers   +10 more
wiley   +1 more source

Hybrid Malware Classification Method Using Segmentation-Based Fractal Texture Analysis and Deep Convolution Neural Network Features

Applied Sciences, 2020
As the number of internet users increases so does the number of malicious attacks using malware. The detection of malicious code is becoming critical, and the existing approaches need to be improved.
Maryam Nisa, Jamal Hussain Shah, Shansa Kanwal, Mudassar Raza, Muhammad Attique Khan, Robertas Damaševičius, Tomas Blažauskas   +6 more
doaj   +1 more source