Tackling class imbalance in computer vision: a contemporary review
Class imbalance is a key issue affecting the performance of computer vision applications
such as medical image analysis, objection detection and recognition, image segmentation …
such as medical image analysis, objection detection and recognition, image segmentation …
A deep learning approach for intrusion detection in Internet of Things using focal loss function
Abstract Internet of Things (IoT) is likely to revolutionize healthcare, energy, education,
transportation, manufacturing, military, agriculture, and other industries. However, for the …
transportation, manufacturing, military, agriculture, and other industries. However, for the …
[HTML][HTML] Focus U-Net: A novel dual attention-gated CNN for polyp segmentation during colonoscopy
Background Colonoscopy remains the gold-standard screening for colorectal cancer.
However, significant miss rates for polyps have been reported, particularly when there are …
However, significant miss rates for polyps have been reported, particularly when there are …
Deep learning algorithm performance in contouring head and neck organs at risk: a systematic review and single-arm meta-analysis
P Liu, Y Sun, X Zhao, Y Yan - BioMedical Engineering OnLine, 2023 - Springer
Purpose The contouring of organs at risk (OARs) in head and neck cancer radiation
treatment planning is a crucial, yet repetitive and time-consuming process. Recent studies …
treatment planning is a crucial, yet repetitive and time-consuming process. Recent studies …
Unmanned aerial vehicle (UAV)-Based pavement image stitching without occlusion, crack semantic segmentation, and quantification
Unmanned Aerial Vehicle (UAV)-based pavement distress detection offers efficient and safe
advantages. However, obstructions from road vehicles and the slender shape of cracks in …
advantages. However, obstructions from road vehicles and the slender shape of cracks in …
Multimodal brain tumor detection using multimodal deep transfer learning
MRI brain image analysis, including brain tumor detection, is a challenging task. MRI images
are multimodal, and in recent years, multimodal medical image analysis has gotten more …
are multimodal, and in recent years, multimodal medical image analysis has gotten more …
Few-shot medical image segmentation using a global correlation network with discriminative embedding
Despite impressive developments in deep convolutional neural networks for medical
imaging, the paradigm of supervised learning requires numerous annotations in training to …
imaging, the paradigm of supervised learning requires numerous annotations in training to …
Automated detection of mechanical damage in flaxseeds using radiographic imaging and machine learning
The growing demand for flaxseed as a source of healthy edible oil mandates the need for
adopting novel strategies for preserving its quantity and quality. Mechanical damage during …
adopting novel strategies for preserving its quantity and quality. Mechanical damage during …
[HTML][HTML] Automatic detection of periapical osteolytic lesions on cone-beam computed tomography using deep convolutional neuronal networks
Introduction Cone-beam computed tomography (CBCT) is an essential diagnostic tool in
oral radiology. Radiolucent periapical lesions (PALs) represent the most frequent jaw …
oral radiology. Radiolucent periapical lesions (PALs) represent the most frequent jaw …
Sd-unet: A novel segmentation framework for ct images of lung infections
S Yin, H Deng, Z Xu, Q Zhu, J Cheng - Electronics, 2022 - mdpi.com
Due to the outbreak of lung infections caused by the coronavirus disease (COVID-19),
humans have to face an unprecedented and devastating global health crisis. Since chest …
humans have to face an unprecedented and devastating global health crisis. Since chest …