Two stage residual CNN for texture denoising and structure enhancement on low dose CT image
Sign Up to like & getrecommendations! Published in 2020 at "Computer methods and programs in biomedicine"
DOI: 10.1016/j.cmpb.2019.105115
Abstract: BACKGROUND AND OBJECTIVE X-ray computed tomography (CT) plays an important role in modern medical science. Human health problems caused by CT radiation have attracted the attention of the academic community widely. Reducing radiation dose results… read more here.
Keywords: image; low dose; ldct images; rcnn ... See more keywords
Deep Learning for Image Sequence Classification of Astronomical Events
Sign Up to like & getrecommendations! Published in 2019 at "Publications of the Astronomical Society of the Pacific"
DOI: 10.1088/1538-3873/aaef12
Abstract: We propose a new sequential classification model for astronomical objects based on a recurrent convolutional neural network (RCNN) which uses sequences of images as inputs. This approach avoids the computation of light curves or difference… read more here.
Keywords: classification; fine tuning; image; rcnn ... See more keywords
A novel concatenate feature fusion RCNN architecture for sEMG-based hand gesture recognition
Sign Up to like & getrecommendations! Published in 2022 at "PLoS ONE"
DOI: 10.1371/journal.pone.0262810
Abstract: Hand gesture recognition tasks based on surface electromyography (sEMG) are vital in human-computer interaction, speech detection, robot control, and rehabilitation applications. However, existing models, whether traditional machine learnings (ML) or other state-of-the-arts, are limited in… read more here.
Keywords: cff rcnn; hand; feature fusion; rcnn ... See more keywords
Evaluation of deep learning methods for early gastric cancer detection using gastroscopic images
Sign Up to like & getrecommendations! Published in 2023 at "Technology and Health Care"
DOI: 10.3233/thc-236027
Abstract: BACKGROUND: A timely diagnosis of early gastric cancer (EGC) can greatly reduce the death rate of patients. However, the manual detection of EGC is a costly and low-accuracy task. The artificial intelligence (AI) method based… read more here.
Keywords: rcnn; detection; deep learning; gastric cancer ... See more keywords
Mass Detection and Segmentation in Digital Breast Tomosynthesis Using 3D-Mask Region-Based Convolutional Neural Network: A Comparative Analysis
Sign Up to like & getrecommendations! Published in 2020 at "Frontiers in Molecular Biosciences"
DOI: 10.3389/fmolb.2020.599333
Abstract: Digital breast tomosynthesis (DBT) is an emerging breast cancer screening and diagnostic modality that uses quasi-three-dimensional breast images to provide detailed assessments of the dense tissue within the breast. In this study, a framework of… read more here.
Keywords: mask rcnn; rcnn; mass detection; breast ... See more keywords
KE-RCNN: Unifying Knowledge based Reasoning into Part-level Attribute Parsing
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on cybernetics"
DOI: 10.48550/arxiv.2206.10146
Abstract: Part-level attribute parsing is a fundamental but challenging task, which requires the region-level visual understanding to provide explainable details of body parts. Most existing approaches address this problem by adding a regional convolutional neural network… read more here.
Keywords: attribute; rcnn; knowledge; part level ... See more keywords