Results 91 to 100 of about 1,721,209 (309)

Deep Learning–Assisted Differentiation of Four Peripheral Neuropathies Using Corneal Confocal Microscopy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Peripheral neuropathies contribute to patient disability but may be diagnosed late or missed altogether due to late referral, limitation of current diagnostic methods and lack of specialized testing facilities. To address this clinical gap, we developed NeuropathAI, an interpretable deep learning–based multiclass classification ...
Chaima Ben Rabah, Ioannis N. Petropoulos, Mark Stettner, Maryam Ferdousi, Uazman Alam, Nathan Efron, Ahmed Serag, Rayaz A. Malik   +7 more
wiley   +1 more source

Network Sketching: Exploiting Binary Structure in Deep CNNs

, 2017
Convolutional neural networks (CNNs) with deep architectures have substantially advanced the state-of-the-art in computer vision tasks. However, deep networks are typically resource-intensive and thus difficult to be deployed on mobile devices. Recently,
Chen, Yurong, Guo, Yiwen, Yao, Anbang, Zhao, Hao   +3 more
core   +1 more source

Developmental, Neuroanatomical and Cellular Expression of Genes Causing Dystonia

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Dystonia is one of the most common movement disorders, with variants in multiple genes identified as causative. However, an understanding of which developmental stages, brain regions, and cell types are most relevant is crucial for developing relevant disease models and therapeutics.
Darren Cameron, Nicholas E. Clifton, Daniel Cabezas de la Fuente, Peter Holmans, Nicholas J. Bray, Kathryn J. Peall   +5 more
wiley   +1 more source

Baseline Regional Cholinergic Denervation Predicts Cognitive Trajectories in Moderate Parkinson Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Cognitive decline is a disabling and variable feature of Parkinson disease (PD). While cholinergic system degeneration is linked to cognitive impairments in PD, most prior research reported cross‐sectional associations. We aimed to fill this gap by investigating whether baseline regional cerebral vesicular acetylcholine transporter ...
Taylor Brown, Giulia Carli, Prabesh Kanel, Stiven Roytman, Jaimie Barr, Nicolaas I. Bohnen, Roger L. Albin   +6 more
wiley   +1 more source

Complex Cryptographic and User‐Centric Physically Unclonable Functions Enabled by Strain‐Sensitive Nanocrystals via Selective Ligand Exchange

Advanced Functional Materials, EarlyView.
This study investigates electromechanical PUFs that improve on traditional electric PUFs. The electron transport materials are coated randomly through selective ligand exchange. It produces multiple keys and a key with motion dependent on percolation and strain, and approaches almost ideal inter‐ and intra‐hamming distances.
Seungshin Lim, Hanseok Seo, Taesung Park, Byung Ku Jung, Junhyeok Park, Young Kyun Choi, Dae Yang Oh, Soong Ju Oh   +7 more
wiley   +1 more source

Exploiting Two‐Photon Lithography, Deposition, and Processing to Realize Complex 3D Magnetic Nanostructures

Advanced Functional Materials, EarlyView.
Two‐photon lithography (TPL) enables 3D magnetic nanostructures with unmatched freedom in geometry and material choice. Advances in voxel control, deposition, and functionalization open pathways to artificial spin ices, racetracks, microrobots, and a number of additional technological applications.
Joseph Askey, Arjen van den Berg, Sandra Ruiz Gomez, Claire Donnelly, Dirk Grundler, Sam Ladak   +5 more
wiley   +1 more source

Training multi-layer binary neural networks with random local binary error signals

Machine Learning: Science and Technology
Binary neural networks (BNNs) significantly reduce computational complexity and memory usage in machine and deep learning by representing weights and activations with just one bit.
Luca Colombo, Fabrizio Pittorino, Manuel Roveri   +2 more
doaj   +1 more source

Searching for Double-line Spectroscopic Binaries in the LAMOST Medium-resolution Spectroscopic Survey with Deep Learning

The Astrophysical Journal Supplement Series, 2023
Double-line spectroscopic binaries (SB2s) are a vital class of spectroscopic binaries for studying star formation and evolution. Searching for SB2s has been a hot topic in astronomy.
Zepeng Zheng, Zhong Cao, Hui Deng, Ying Mei, Lei Tan, Feng Wang   +5 more
doaj   +1 more source

Deterministic Binary Filters for Convolutional Neural Networks [PDF]

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018
We propose Deterministic Binary Filters, an approach to Convolutional Neural Networks that learns weighting coefficients of predefined orthogonal binary basis instead of the conventional approach of learning directly the convolutional filters. This approach results in model architectures with significantly fewer parameters (4x to 16x) and smaller model
Tseng, V, Bhattachara, S, Fernández-Marqués, J, Alizadeh, M, Tong, C, Lane, N   +5 more
openaire   +1 more source

A Smart Magnetically Actuated Flip‐Disc Programmable Metasurface with Ultralow Power Consumption for Real‐Time Channel Control

Advanced Functional Materials, EarlyView.
The study proposes a 1‐bit programmable metasurface based on flip‐disc display, named flip‐disc metasurface (FD‐MTS). This new design enables ultralow energy consumption while maintaining coding patterns. It also exhibits high scalability and multifunctional flexibility.
Jiang Han Bao, Che Liu, Jia Cheng Li, Zhen Hao Fu, Yi Su Huang, Si Qi Huang, Lei Zhang, Jian Wei You, Tie Jun Cui   +8 more
wiley   +1 more source