Results 71 to 80 of about 609,343 (292)
Multimodal Sensing for Depression Risk Detection: Integrating Audio, Video, and Text Data
Depression is a major psychological disorder with a growing impact worldwide. Traditional methods for detecting the risk of depression, predominantly reliant on psychiatric evaluations and self-assessment questionnaires, are often criticized for their ...
Zhenwei Zhang +12 more
doaj +1 more source
Using SenseCam images in a multimodal fusion framework for route detection and localisation [PDF]
Problem of structuring location data is solved by proposing a framework for classifying the data into often-traversed routes. It does not rely on any one source of location information, but can fuse data from multimodal localisation sources: SenseCam ...
Brennan, Conor +2 more
core
Value of MRI Outcomes for Preventive and Early‐Stage Trials in Spinocerebellar Ataxias 1 and 3
ABSTRACT Objective To examine the value of MRI outcomes as endpoints for preventive and early‐stage trials of two polyglutamine spinocerebellar ataxias (SCAs). Methods A cohort of 100 participants (23 SCA1, 63 SCA3, median Scale for the Assessment and Rating of Ataxia (SARA) score = 5, 42% preataxic, and 14 gene‐negative controls) was scanned at 3T up ...
Thiago J. R. Rezende +26 more
wiley +1 more source
LIDAR-Camera Fusion for Road Detection Using Fully Convolutional Neural Networks
In this work, a deep learning approach has been developed to carry out road detection by fusing LIDAR point clouds and camera images. An unstructured and sparse point cloud is first projected onto the camera image plane and then upsampled to obtain a set
Bellone, Mauro +3 more
core +1 more source
Fluid Biomarkers of Disease Burden and Cognitive Dysfunction in Progressive Supranuclear Palsy
ABSTRACT Objective Identifying objective biomarkers for progressive supranuclear palsy (PSP) is crucial to improving diagnosis and establishing clinical trial and treatment endpoints. This study evaluated fluid biomarkers in PSP versus controls and their associations with regional 18F‐PI‐2620 tau‐PET, clinical, and cognitive outcomes.
Roxane Dilcher +10 more
wiley +1 more source
Deep Multimodal Speaker Naming
Automatic speaker naming is the problem of localizing as well as identifying each speaking character in a TV/movie/live show video. This is a challenging problem mainly attributes to its multimodal nature, namely face cue alone is insufficient to achieve
Dai, Jingwen +5 more
core +1 more source
ABSTRACT Background Emerging evidence suggests that low‐frequency neural oscillations are dynamically regulated by consciousness levels, with the recovery of low cortical activity potentially serving as a neurophysiological substrate for conscious emergence. Targeted enhancement of these low‐frequency rhythms in patients with disorders of consciousness
Chuan Xu +10 more
wiley +1 more source
Statistical modeling of univariate multimodal data
Unimodality constitutes a key property indicating grouping behavior of the data around a single mode of its density. We propose a method that partitions univariate data into unimodal subsets through recursive splitting around valley points of the data density.
Paraskevi Chasani, Aristidis Likas
openaire +2 more sources
Multidimensional Profiling of MRI‐Negative Temporal Lobe Epilepsy Uncovers Distinct Phenotypes
ABSTRACT Objective Although hippocampal sclerosis (TLE‐HS) represents the most frequent cause of temporal lobe epilepsy (TLE), up to 30% of patients show no lesion on visual MRI inspection (TLE‐MRIneg). These cases pose diagnostic and therapeutic challenges and are underrepresented in surgical series.
Alice Ballerini +28 more
wiley +1 more source
Multistep Networks for Deformable Multimodal Medical Image Registration
We proposed neural networks for deformable multimodal medical image registration that use multiple steps and varying resolutions. The networks were trained jointly in an unsupervised manner with Mutual Information and Gradient L2 loss.
Anika Strittmatter, Frank G. Zollner
doaj +1 more source

