Results 121 to 130 of about 3,835,189 (296)

Leveraging Contextual Information for Monocular Depth Estimation

open access: yes, 2020
Humans strongly rely on visual cues to understand scenes such as segmenting, detecting objects, or measuring the distance from nearby objects. Recent studies suggest that deep neural networks can take advantage of contextual representation for the ...
Kim, Doyeon   +3 more
core   +1 more source

Anticoagulation Treatment Response Among Phenotypic ESUS Clusters: Evidence From CASPR

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To evaluate treatment effect heterogeneity across phenotypic clusters of patients with cryptogenic embolic stroke using causal inference methods. Methods From a retrospective, multicenter cohort of patients with cryptogenic embolic stroke, we estimated the treatment effect of anticoagulation versus antiplatelet therapy in patients ...
Elena Badillo Goicoechea   +53 more
wiley   +1 more source

Diffusion Basis Spectrum Imaging of Tissue Microstructure and Early Treatment in Multiple Sclerosis

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Conventional MRI cannot resolve the coexisting pathological processes within multiple sclerosis tissue. Diffusion Basis Spectrum Imaging decomposes the diffusion signal into fiber, cell, and hindered ratios indexing axonal integrity, cellularity, and extracellular space, respectively.
Apisit Kaewsanit   +10 more
wiley   +1 more source

Artificial Intelligence–Based Online Symptom Assessment Tools for Systemic Lupus Erythematosus Diagnosis: Patient Perspectives

open access: yesArthritis Care &Research, EarlyView.
Objective The objective of this article is to identify perceptions of patients with systemic lupus erythematosus (SLE) regarding artificial intelligence (AI)–based online symptom assessment tools, and the potential of these tools to address diagnostic barriers.
Olivia A. Stein   +7 more
wiley   +1 more source

Image depth estimation assisted by multi-view projection

open access: yesComplex & Intelligent Systems
In recent years, deep learning has significantly advanced the development of image depth estimation algorithms. The depth estimation network with single-view input can only extract features from a single 2D image, often neglecting the information ...
Liman Liu   +6 more
doaj   +1 more source

Monocular 3D object detection with thermodynamic loss and decoupled instance depth

open access: yesConnection Science
Monocular 3D detection is to obtain the 3D information of the object from the image. The mainstream methods mainly use L1 loss or L1-like loss to control the instance depth prediction. However, these methods have not achieved satisfactory results. One of
Gang Liu, Xiaoxiao Xie, Qingchen Yu
doaj   +1 more source

Depth-based adaptive search range algorithm for motion estimation in HEVC

open access: yes, 2014
High efficient video coding has been developed for ultra-high resolution and multi-view videos. It doubles the compression ratio compared to H.264/MPEG-4 AVC, but requires to adopt a very high computational quad-tree structure in motion estimation ...
Yui-Lam Chan (13527556)   +2 more
core  

The Gut–Heart Axis in Systemic Sclerosis: Evidence From a Large Prospective Early Disease Cohort

open access: yesArthritis Care &Research, EarlyView.
Objective Cardiac involvement significantly impacts prognosis in systemic sclerosis (SSc), highlighting the need for early risk stratification. Gastrointestinal (GI) symptoms are common and often manifest early. Emerging data suggest a link between GI and cardiac manifestations, possibly through shared mechanisms like dysautonomia.
Francesca R. Di Ciommo   +9 more
wiley   +1 more source

Mode sign estimation to improve source depth estimation

open access: yes, 2008
International audienceThis paper describes source depth estimation in shallow water environments using a Horizontal Line Array of hydro\-phones on the sea bottom.
Gregoire Le Touze   +5 more
core   +1 more source

Engagement Patterns With an Artificial Intelligence Health Coach for Systemic Sclerosis Self‐Management: A Mixed Methods Study

open access: yesArthritis Care &Research, EarlyView.
Objective To evaluate utility of an artificial intelligence (AI) health coach for systemic sclerosis (SSc) self‐management and identify patterns associated with participant engagement. Methods We conducted a mixed methods study in which an AI health coach, powered by a large language model (LLM), was used to support self‐management for SSc.
Nirali Shah   +4 more
wiley   +1 more source

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