Machine learning techniques for the Schizophrenia diagnosis: a comprehensive review and future research directions
Schizophrenia (SCZ) is a brain disorder where different people experience different
symptoms, such as hallucination, delusion, flat-talk, disorganized thinking, etc. In the long …
symptoms, such as hallucination, delusion, flat-talk, disorganized thinking, etc. In the long …
Domain shift in computer vision models for MRI data analysis: an overview
E Kondrateva, M Pominova, E Popova… - … on Machine Vision, 2021 - spiedigitallibrary.org
Machine learning and computer vision methods are showing good performance in medical
imagery analysis. Yet only a few applications are now in clinical use and one of the reasons …
imagery analysis. Yet only a few applications are now in clinical use and one of the reasons …
Deformable 3d convolution for video super-resolution
The spatio-temporal information among video sequences is significant for video super-
resolution (SR). However, the spatio-temporal information cannot be fully used by existing …
resolution (SR). However, the spatio-temporal information cannot be fully used by existing …
DC2Net: An Asian Soybean Rust Detection Model Based on Hyperspectral Imaging and Deep Learning
J Feng, S Zhang, Z Zhai, H Yu, H Xu - Plant Phenomics, 2024 - spj.science.org
Asian soybean rust (ASR) is one of the major diseases that causes serious yield loss
worldwide, even up to 80%. Early and accurate detection of ASR is critical to reduce …
worldwide, even up to 80%. Early and accurate detection of ASR is critical to reduce …
ALA-Net: Adaptive lesion-aware attention network for 3D colorectal tumor segmentation
Accurate and reliable segmentation of colorectal tumors and surrounding colorectal tissues
on 3D magnetic resonance images has critical importance in preoperative prediction …
on 3D magnetic resonance images has critical importance in preoperative prediction …
Deep‐learning based fully automatic segmentation of the globus pallidus interna and externa using ultra‐high 7 Tesla MRI
Deep brain stimulation (DBS) surgery has been shown to dramatically improve the quality of
life for patients with various motor dysfunctions, such as those afflicted with Parkinson's …
life for patients with various motor dysfunctions, such as those afflicted with Parkinson's …
Factornet: Holistic actor, object, and scene factorization for action recognition in videos
The ability to recognize human actions in a video is challenging due to the complex nature
of video data and the subtlety of human actions. Human activities often get associated with …
of video data and the subtlety of human actions. Human activities often get associated with …
Multi-scale deep information and adaptive attention mechanism based coronary reconstruction of superior mesenteric artery
K Zhang, Y Han, P Xu, M Wang, J Yang, P Lin… - IEEE …, 2023 - ieeexplore.ieee.org
Vascular images contain a lot of key information, such as length, diameter and distribution.
Thus reconstruction of vessels such as the Superior Mesenteric Artery is critical for the …
Thus reconstruction of vessels such as the Superior Mesenteric Artery is critical for the …
CoviNet: Covid-19 diagnosis using machine learning analyses for computerized tomography images
The Covid-19 is a highly contagious and virulent disease caused by the Severe Acute
Respiratory Syndrome-Corona Virus–2 (SARS-CoV-2). Over 146 million cases and 3.1 …
Respiratory Syndrome-Corona Virus–2 (SARS-CoV-2). Over 146 million cases and 3.1 …
3D deformable convolution for action classification in videos
Action recognition is one of the popular research areas in computer vision because it can be
applied to solve many problems especially in security surveillance, behavior analysis …
applied to solve many problems especially in security surveillance, behavior analysis …