Covid-caps: A capsule network-based framework for identification of covid-19 cases from x-ray images
Abstract Novel Coronavirus disease (COVID-19) has abruptly and undoubtedly changed the
world as we know it at the end of the 2nd decade of the 21st century. COVID-19 is extremely …
world as we know it at the end of the 2nd decade of the 21st century. COVID-19 is extremely …
Review of deep learning approaches for the segmentation of multiple sclerosis lesions on brain MRI
In recent years, there have been multiple works of literature reviewing methods for
automatically segmenting multiple sclerosis (MS) lesions. However, there is no literature …
automatically segmenting multiple sclerosis (MS) lesions. However, there is no literature …
Real-time detection of cracks in tiled sidewalks using YOLO-based method applied to unmanned aerial vehicle (UAV) images
The conventional method of manually verifying the quality of tiled sidewalks is laborious,
because of the time-consuming identification of cracks from numerous grid-like elements of …
because of the time-consuming identification of cracks from numerous grid-like elements of …
Deep learning-based point-scanning super-resolution imaging
Point-scanning imaging systems are among the most widely used tools for high-resolution
cellular and tissue imaging, benefiting from arbitrarily defined pixel sizes. The resolution …
cellular and tissue imaging, benefiting from arbitrarily defined pixel sizes. The resolution …
Brain tumor MR image classification using convolutional dictionary learning with local constraint
Brain tumor image classification is an important part of medical image processing. It assists
doctors to make accurate diagnosis and treatment plans. Magnetic resonance (MR) imaging …
doctors to make accurate diagnosis and treatment plans. Magnetic resonance (MR) imaging …
Pixel‐level thin crack detection on road surface using convolutional neural network for severely imbalanced data
T Siriborvornratanakul - Computer‐Aided Civil and …, 2023 - Wiley Online Library
Because roads are the major backbone of the transportation network, research about crack
detection on road surfaces has been popular in computer and infrastructure engineering …
detection on road surfaces has been popular in computer and infrastructure engineering …
Systematic review with meta‐analysis: artificial intelligence in the diagnosis of oesophageal diseases
Background Artificial intelligence (AI) has recently been applied to endoscopy and
questionnaires for the evaluation of oesophageal diseases (ODs). Aim We performed a …
questionnaires for the evaluation of oesophageal diseases (ODs). Aim We performed a …
Autofocusing technologies for whole slide imaging and automated microscopy
Whole slide imaging (WSI) has moved digital pathology closer to diagnostic practice in
recent years. Due to the inherent tissue topography variability, accurate autofocusing …
recent years. Due to the inherent tissue topography variability, accurate autofocusing …
Towards open-set touchless palmprint recognition via weight-based meta metric learning
Touchless biometrics has become significant in the wake of novel coronavirus 2019 (COVID-
19). Due to the convenience, user-friendly, and high-accuracy, touchless palmprint …
19). Due to the convenience, user-friendly, and high-accuracy, touchless palmprint …
O-Net: a novel framework with deep fusion of CNN and transformer for simultaneous segmentation and classification
The application of deep learning in the medical field has continuously made huge
breakthroughs in recent years. Based on convolutional neural network (CNN), the U-Net …
breakthroughs in recent years. Based on convolutional neural network (CNN), the U-Net …