Results 111 to 120 of about 120,084 (296)

A communication-efficient distributed deep learning remote sensing image change detection framework

International Journal of Applied Earth Observations and Geoinformation
With the introduction of deep learning methods, the computation required for remote sensing change detection has significantly increased, and distributed computing is applied to remote sensing change detection to improve computational efficiency. However,
Hongquan Cheng, Jie Zheng, Huayi Wu, Kunlun Qi, Lihua He   +4 more
doaj   +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

No Peek: A Survey of private distributed deep learning

CoRR, 2018
We survey distributed deep learning models for training or inference without accessing raw data from clients. These methods aim to protect confidential patterns in data while still allowing servers to train models. The distributed deep learning methods of federated learning, split learning and large batch stochastic gradient descent are compared in ...
Praneeth Vepakomma, Tristan Swedish, Ramesh Raskar, Otkrist Gupta, Abhimanyu Dubey   +4 more
openaire   +2 more sources

Cognitive and Neuroimaging Divergence Between Juvenile and Adult FUS Amyotrophic Lateral Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder characterized by progressive motor neuron degeneration. Fused in sarcoma (FUS)‐associated juvenile ALS (jALS) represents a distinct and aggressive subgroup with rapid deterioration and poor prognosis.
Alexandra V. Jürs, Marcel Naumann, Annaliis Lehto, Hanna Schön, Jens Kurth, Johannes Prudlo, Andreas Hermann, Elisabeth Kasper   +7 more
wiley   +1 more source

Digital Cognitive Phenotyping for Differential Diagnosis and Monitoring in Neurological Conditions

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To assess the utility, accessibility, and equivalence to supervised scales of online cognitive assessment in older individuals with cognitive impairment. Methods Patients with Alzheimer's disease (AD, n = 31), idiopathic normal pressure hydrocephalus (iNPH, n = 26), and traumatic brain injury (TBI, n = 23) completed online cognitive ...
Martina Del Giovane, Valentina Giunchiglia, Michael C. B. David, Magdalena A. Kolanko, William R. Trender, Peter J. Hellyer, Harmeena Kaur, David J. Sharp, Christopher Carswell, Paresh A. Malhotra, Adam Hampshire   +10 more
wiley   +1 more source

Exploring NCCL Tuning Strategies for Distributed Deep Learning

The communication overhead in distributed deep learning caused by the synchronization of model parameters across multiple devices can significantly impact training time.
Salimi Beni, Majid; orcid:, Hunold, Sascha; orcid:, Cosenza, Biagio; orcid:, Laso, Ruben; orcid:, Benkner, Siegfried; orcid:   +4 more
core   +1 more source

Low-Scalability Distributed Systems for Artificial Intelligence: A Comparative Study of Distributed Deep Learning Frameworks for Image Classification

Applied Sciences
Artificial intelligence has experienced tremendous growth in various areas of knowledge, especially in computer science. Distributed computing has become necessary for storing, processing, and generating large amounts of information essential for ...
Manuel Rivera-Escobedo, Manuel de Jesús López-Martínez, Luis Octavio Solis-Sánchez, Héctor Alonso Guerrero-Osuna, Sodel Vázquez-Reyes, Daniel Acosta-Escareño, Carlos A. Olvera-Olvera   +6 more
doaj   +1 more source

Distributional refinement network: Distributional forecasting via deep learning

Insurance: Mathematics and Economics
A key task in actuarial modelling involves modelling the distributional properties of losses. Classic (distributional) regression approaches like Generalized Linear Models (GLMs; Nelder and Wedderburn, 1972) are commonly used, but challenges remain in developing models that can (i) allow covariates to flexibly impact different aspects of the ...
Benjamin Avanzi, Eric T. Dong, Patrick J. Laub, Bernard Wong   +3 more
openaire   +2 more sources

Upper Cervical Cord Area as a Biomarker of Conversion to Secondary Progressive Multiple Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective This study assessed whether upper cervical cord area (UCCA) measured on routine brain MRI can serve as a biomarker of conversion to SPMS. Methods This is a single‐center retrospective cohort study of RRMS patients with cross‐sectional and longitudinal analyses of clinical and MRI data. Future SPMS converters were matched by age, sex,
Nabil K. El Ayoubi, Sola Al Ghazal, Salem Hannoun, Medhat A. Siddik, Nour M. Najjar, Jim Dagher, Joseph Abboud, Myriam G. Semaan, Samia J. Khoury   +8 more
wiley   +1 more source

TrustDDL: A Privacy-Preserving Byzantine-Robust Distributed Deep Learning Framework

This paper introduces a distributed deep learning framework called TrustDDL crafted to address privacy and Byzantine robustness concerns across the training and inference phases of deep learning models.
Mirabi, Meghdad, Binnig, Carsten, Nikiel, René Klaus   +2 more
core   +1 more source