Results 71 to 80 of about 22,800 (222)

A Double Dwell High Sensitivity GPS Acquisition Scheme Using Binarized Convolution Neural Network

Sensors, 2018
Conventional GPS acquisition methods, such as Max selection and threshold crossing (MAX/TC), estimate GPS code/Doppler by its correlation peak. Different from MAX/TC, a multi-layer binarized convolution neural network (BCNN) is proposed to recognize the ...
Zhen Wang, Yuan Zhuang, Jun Yang, Hengfeng Zhang, Wei Dong, Min Wang, Luchi Hua, Bo Liu, Longxing Shi   +8 more
doaj   +1 more source

Allosteric Modulation of Pathological Ataxin‐3 Aggregation: A Path to Spinocerebellar Ataxia Type‐3 Therapies

Advanced Science, EarlyView.
This study uncovers a new allosteric site in the Josephin domain of ataxin‐3 targeted by the molecular tweezer CLR01, which modulates protein aggregation, improves synaptic function in neuronal cells, and delays motor dysfunction in animal models.
Alexandra Silva, Sara Duarte‐Silva, Pedro M. Martins, Beatriz Rodrigues, Débora Serrenho, Daniela Vilasboas‐Campos, Andreia Teixeira‐Castro, Julio Vieyto‐Nuñez, Joel Mieres‐Perez, Francisco Figueiredo, Martyna Podlasiak, Tatiana Van‐der‐Kellen, Joana Fraga, James Noble, Carter Lantz, Niki Sepanj, Daniela Monteiro‐Fernandes, Sara Guerreiro, Andreia Neves‐Carvalho, Joana Pereira‐Sousa, Frank‐Gerrit Klärner, Thomas Schrader, Joseph A. Loo, Annalisa Pastore, Elsa Sanchez‐Garcia, Gal Bitan, Ana Luísa Carvalho, Patrícia Maciel, Sandra Macedo‐Ribeiro   +28 more
wiley   +1 more source

Searching Similarity Measure for Binarized Neural Networks

, 2022
Being a promising model to be deployed in resource-limited devices, Binarized Neural Networks (BNNs) have drawn extensive attention from both academic and industry. However, comparing to the full-precision deep neural networks (DNNs), BNNs suffer from non-trivial accuracy degradation, limiting its applicability in various domains.
Li, Yanfei, Li, Ang, Yu, Huimin
openaire   +2 more sources

A new approach to binarizing neural networks [PDF]

2016 International SoC Design Conference (ISOCC), 2016
As deep neural networks grow larger, they suffer from a huge number of weights, and thus reducing the overhead of handling those weights becomes one of key challenges nowadays. This paper presents a new approach to binarizing neural networks, where the weights are pruned and forced to take degenerate binary values.
Jungwoo Seo, Joonsang Yu, Jongeun Lee, Kiyoung Choi   +3 more
openaire   +1 more source

Integrated Transcriptomics Reveals Evolutionary Trajectories and Cell Density‐Dependent Mechanisms in Aldosterone‐Producing Adenomas

Advanced Science, EarlyView.
Aldosterone‐producing adenomas (APAs) develop via two distinct paths: directly from adrenal zona glomerulosa (zG) cells, or stepwise from zG cells through aldosterone‐producing micronodules (APMs) before progressing to APAs. Advanced single‐cell and spatial analyses identified distinct cell states linked to oxidative stress and cell–cell interactions ...
Zhuolun Sun, Changying Jing, Martina Tetti, Siyuan Gong, Jia Wei, Yingxian Pang, Martin Reincke, Tracy Ann Williams   +7 more
wiley   +1 more source

Sweetspot Mapping in Deep Brain Stimulation: Strengths and Limitations of Current Approaches

Neuromodulation: Technology at the Neural Interface, EarlyView., 2021
Abstract Objectives Open questions remain regarding the optimal target, or sweetspot, for deep brain stimulation (DBS) in, for example, Parkinson's disease. Previous studies introduced different methods of mapping DBS effects to determine sweetspots. While having a direct impact on surgical targeting and postoperative programming in DBS, these methods ...
Till A. Dembek, Juan Carlos Baldermann, Jan‐Niklas Petry‐Schmelzer, Hannah Jergas, Harald Treuer, Veerle Visser‐Vandewalle, Haidar S. Dafsari, Michael T. Barbe   +7 more
wiley   +1 more source

A Multi-Class ECG Signal Classifier Using a Binarized Depthwise Separable CNN with the Merged Convolution–Pooling Method

Sensors
Binarized convolutional neural networks (bCNNs) are favored for the design of low-storage, low-power cardiac arrhythmia classifiers owing to their high weight compression rate.
Rui Zhang, Ranran Zhou, Zuting Zhong, Haifeng Qi, Yong Wang   +4 more
doaj   +1 more source

FINN: A Framework for Fast, Scalable Binarized Neural Network Inference

, 2016
Research has shown that convolutional neural networks contain significant redundancy, and high classification accuracy can be obtained even when weights and activations are reduced from floating point to binary values.
Blott, Michaela, Fraser, Nicholas J., Gambardella, Giulio, Jahre, Magnus, Leong, Philip, Umuroglu, Yaman, Vissers, Kees   +6 more
core   +1 more source

A Virtual Clinical Trial of Psychedelics to Treat Patients With Disorders of Consciousness

Advanced Science, EarlyView.
Disorders of consciousness after severe brain injury are marked by reduced complexity of brain activity and limited treatment options. Using personalized whole‐brain models, this study shows that simulated lysergic acid diethylamide (LSD) and psilocybin shift patient brain dynamics closer to criticality.
Naji L.N. Alnagger, Paolo Cardone, Charlotte Martial, Yonatan Sanz Perl, Iván Mindlin, Jacobo D Sitt, Leor Roseman, Robin Carhart‐Harris, David Nutt, Pablo Mallaroni, Natasha Mason, Johannes G Ramaekers, Vincent Bonhomme, Steven Laureys, Gustavo Deco, Olivia Gosseries, Pablo Núñez, Jitka Annen   +17 more
wiley   +1 more source

A Novel Optical/digital Processing System for Pattern Recognition [PDF]

, 1993
This paper describes two processing algorithms that can be implemented optically: the Radon transform and angular correlation. These two algorithms can be combined in one optical processor to extract all the basic geometric and amplitude features from ...
Boone, Bradley G., Shukla, Oodaye B.
core   +1 more source