Results 101 to 110 of about 218,844 (266)

Deep Learning as Applied in SAR Target Recognition and Terrain Classification

Leida xuebao, 2017
Deep learning such as deep neural networks has revolutionized the computer vision area. Deep learning-based algorithms have surpassed conventional algorithms in terms of performance by a significant margin. This paper reviews our works in the application
Xu Feng, Wang Haipeng, Jin Yaqiu
doaj   +1 more source

Dissection of Deep Neural Networks.

, 2021
We investigate the role of neurons within the internal computations of deep neural networks for computer vision. We introduce network dissection, a method for quantifying the alignment between human-interpretable visual concepts and individual neurons in a deep network.
openaire   +1 more source

Evaluation of Digital Technologies for Home‐Based Assessment in People With Amyotrophic Lateral Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Digital technologies hold promise for transforming healthcare by enhancing personalized treatments and offer valuable opportunities to improve patient care. Here, we evaluated several novel, self‐administered, home‐based, digital endpoints for their association with corresponding conventional standard clinical measures (primary) in ...
Arne Mueller, Vanessa Vallejo, Mónica Povedano Panadés, Orla Hardiman, Véronique Danel‐Brunaud, Senda Ajroud‐Driss, Philippe Couratier, Jeremy Shefner, Anna Gokey, Mike DiCesare, Erin Lennox, Jens Praestgaard, Lucie Brujin, Peggy Allred, Ram Miller   +14 more
wiley   +1 more source

Sex‐Stratified Association of Regional Dopamine Transporter Binding With Disease Progression in Amyotrophic Lateral Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To clarify the clinical relevance of dopamine transporter single‐photon emission computed tomography (DAT‐SPECT) abnormalities in amyotrophic lateral sclerosis (ALS), with a prespecified focus on sex‐stratified associations with disease progression and short‐term prognosis.
Tomoya Kawazoe, Keizo Sugaya, Kentaro Hayashi, Keiko Hino, Yasuhiro Nakata, Kota Bokuda, Toshio Shimizu, Kazushi Takahashi   +7 more
wiley   +1 more source

Onasemnogene Abeparvovec in Patients With SMA: Interim Results of the RESTORE Registry in Japan

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective There are limited real‐world data regarding the safety and effectiveness of onasemnogene abeparvovec (OA; Zolgensma) infusion, a one‐time gene replacement therapy, for Japanese patients with spinal muscular atrophy (SMA). We aimed to improve understanding of the real‐world outcomes for OA in Japan.
Kayoko Saito, Kamal Benguerba, Ken Tsuchida, Kazushige Yazawa, Isao Tsumiyama, Hiromitsu Kayama, Sandra P. Reyna, Farid Khan, Richard S. Finkel   +8 more
wiley   +1 more source

Uncovering G Protein‐Coupled Receptors: Novel Targets and Biomarkers for Predicting Glioma Prognosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Low‐grade gliomas (LGG) exhibit significant heterogeneity and recurrence risk. G protein‐coupled receptors (GPCR) contribute to glioma malignant progression, but their prognostic value remains unclear. This work attempts to formulate a GPCR‐based outcome‐predicting model for LGG. Methods Based on TCGA LGG data, the enrichment scores
Jun Yang, Dongxu Zhang, Dongyuan Liu, Da Lin, Hao Wang   +4 more
wiley   +1 more source

Thalamo‐Lesional Connectivity Signatures of Bilateral Tonic–Clonic Seizures in Focal Cortical Dysplasia‐Related Epilepsy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives Focal cortical dysplasia (FCD) is the most common etiology of drug‐resistant epilepsy in children. Focal to bilateral tonic–clonic seizures (FBTCS) mark a high risk of drug‐resistant epilepsy and involve thalamocortical circuitry in their generation and propagation.
Hua Xie, Xiaotong Li, Venkata Sita Priyanka Illapani, Leigh N. Sepeta, Jason Schroeder, Chima O. Oluigbo, Madison M. Berl, William D. Gaillard, Nathan T. Cohen   +8 more
wiley   +1 more source

A survey of efficient deep neural network

Dianxin kexue, 2020
Recently,deep neural network (DNN) has achieved great success in the field of AI such as computer vision and natural language processing.Thanks to a deeper and larger network structure,DNN’s performance is rapidly increasing.However,deeper and lager deep
Rui MIN
doaj   +2 more sources

Blood RNA Biomarker Signatures for Early Diagnosis and Prognosis in Ischemic and Hemorrhagic Stroke: The IBIS‐CT1 Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To evaluate the expression of nine blood RNA biomarkers in a clinical trial based on genes previously identified in an experimental monkey model of stroke for diagnosis feasibility and prognostication. Methods IBIS‐CT1 was a prospective longitudinal study enrolling patients with ischemic stroke (IS) or intracerebral hemorrhage (ICH ...
Salomé Retailleau, Marie Bruguet, Irina Viakhireva‐Dovganyuk, François‐Mathias Merrien, Denis Marechal, Aurore Jourdain, Philippe Goas, Jordan Coris, Julien Asselineau, Maëlys Consigny, Gérald Le Gac, Serge Timsit   +11 more
wiley   +1 more source

Efficient Deep Neural Networks

CoRR, 2019
The success of deep neural networks (DNNs) is attributable to three factors: increased compute capacity, more complex models, and more data. These factors, however, are not always present, especially for edge applications such as autonomous driving, augmented reality, and internet-of-things.
openaire   +2 more sources