Results 51 to 60 of about 56,385 (248)

Crowd counting with segmentation attention convolutional neural network

open access: yesIET Image Processing, 2021
Deep learning occupies an undisputed dominance in crowd counting. This paper proposes a novel convolutional neural network architecture called SegCrowdNet.
Jiwei Chen, Zengfu Wang
doaj   +1 more source

Subclinical Optic Nerve Involvement in Radiologically Isolated Syndrome: Multimodal Detection and Diagnostic Impact

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives We aimed to determine the frequency of subclinical optic nerve (ON) lesions using MRI, optical coherence tomography (OCT), and visual evoked potentials (VEP) in radiologically isolated syndrome (RIS), and to assess their diagnostic and prognostic significance.
Christine Lebrun‐Frenay   +13 more
wiley   +1 more source

End‐to‐end feature fusion Siamese network for adaptive visual tracking

open access: yesIET Image Processing, 2021
According to observations, different visual objects have different salient features in different scenarios. Even for the same object, its salient shape and appearance features may change greatly from time to time in a long‐term tracking task.
Dongyan Guo   +5 more
doaj   +1 more source

Natural Frequencies of Levodopa‐Induced Dyskinesia in Parkinson's Disease

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives Abnormal involuntary movements, known as dyskinesias, are common complications of levodopa treatment in patients with Parkinson's disease and can significantly impair quality of life. The underlying pathophysiology remains unclear, and current therapeutic options are limited.
Ioannis U. Isaias   +3 more
wiley   +1 more source

Polarimetric dynamic vision sensor p(DVS) neural network architecture for motion classification

open access: yesElectronics Letters, 2021
The purpose of this study is to introduce efficient bio‐inspired vision architectures, integrating human cognition capabilities, such as computation and memory emulating neurons and synapses, together with polarization of light properties, that would ...
Martin Nowak   +6 more
doaj   +1 more source

Artificial Intelligence in Systemic Sclerosis: Clinical Applications, Challenges, and Future Directions

open access: yesArthritis Care &Research, EarlyView.
Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos   +2 more
wiley   +1 more source

An improved symbol reduction technique based Huffman coder for efficient entropy coding in the transform coders

open access: yesIET Image Processing, 2021
Entropy coding is the essential block of transform coders that losslessly converts the quantized transform coefficients into the bit‐stream suitable for transmission or storage.
Vikrant Singh Thakur   +2 more
doaj   +1 more source

What Do Large Language Models Know About Materials?

open access: yesAdvanced Engineering Materials, EarlyView.
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer   +2 more
wiley   +1 more source

Dense connection decoding network for crisp contour detection

open access: yesIET Image Processing, 2021
In the past few years, contour detection algorithm has made obvious progress with the help of convolutional neural networks. The aim of this paper is to present a novel network connecting low‐ and high‐resolution features to make the network achieving ...
Guili Xu, Chuan Lin, Yuehua Cheng
doaj   +1 more source

NFDI MatWerk Ontology (MWO): A BFO‐Compliant Ontology for Research Data Management in Materials Science and Engineering

open access: yesAdvanced Engineering Materials, EarlyView.
This article presents the NFDI‐MatWerk Ontology (MWO), a Basic Formal Ontology‐based framework for interoperable research data management in materials science and engineering (MSE). Covering consortium structures, research data management resources, services, and instruments, MWO enables semantic integration, Findable, Accessible, Interoperable, and ...
Hossein Beygi Nasrabadi   +4 more
wiley   +1 more source

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