Results 61 to 70 of about 377,372 (346)
Investigating the Potential of Network Optimization for a Constrained Object Detection Problem
Journal of Imaging, 2021 Object detection models are usually trained and evaluated on highly complicated, challenging academic datasets, which results in deep networks requiring lots of computations. However, a lot of operational use-cases consist of more constrained situations:
Tanguy Ophoff +3 more
doaj +1 more source
Distilled Gradual Pruning With Pruned Fine-Tuning
IEEE Transactions on Artificial IntelligenceNeural networks (NNs) have been driving machine learning progress in recent years, but their larger models present challenges in resource-limited environments. Weight pruning reduces the computational demand, often with performance degradation and long training procedures.
Federico Fontana +6 more
openaire +3 more sources
, 2017 When approaching a novel visual recognition problem in a specialized image domain, a common strategy is to start with a pre-trained deep neural network and fine-tune it to the specialized domain.
Mori, Greg +2 more
core +1 more source
Diffusion Tractography Biomarker for Epilepsy Severity in Children With Drug‐Resistant Epilepsy
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To develop a novel deep‐learning model of clinical DWI tractography that can accurately predict the general assessment of epilepsy severity (GASE) in pediatric drug‐resistant epilepsy (DRE) and test if it can screen diverse neurocognitive impairments identified through neuropsychological assessments.
Jeong‐Won Jeong +7 more
wiley +1 more source
Text Classification Using Association Rules, Dependency Pruning and Hyperonymization
, 2014 We present new methods for pruning and enhancing item- sets for text classification via association rule mining. Pruning methods are based on dependency syntax and enhancing methods are based on replacing words by their hyperonyms of various orders.
Haralambous, Yannis, Lenca, Philippe
core +3 more sources
LD-Pruner: Efficient Pruning of Latent Diffusion Models using Task-Agnostic Insights [PDF]
2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)Latent Diffusion Models (LDMs) have emerged as powerful generative models, known for delivering remarkable results under constrained computational resources.
Thibault Castells +3 more
semanticscholar +1 more source
Functional Connectivity Linked to Cognitive Recovery After Minor Stroke
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Patients with minor stroke exhibit slowed processing speed and generalized alterations in functional connectivity involving frontoparietal cortex (FPC). The pattern of connectivity evolves over time. In this study, we examine the relationship of functional connectivity patterns to cognitive performance, to determine ...
Vrishab Commuri +7 more
wiley +1 more source
Food and Energy SecurityThis study aimed to investigate the effects of pruning period and intensity on the growth and yield of Rosa roxburghii Tratt, a shrub fruit species with significant economic value, to inform optimized pruning practices for its cultivation and management.
Yangzhou Xiang +5 more
doaj +1 more source
Symbolic dynamics I. Finite dispersive billiards
, 1993 Orbits in different dispersive billiard systems, e.g. the 3 disk system, are mapped into a topological well ordered symbol plane and it is showed that forbidden and allowed orbits are separated by a monotone pruning front.
Hansen, Kai T.
core +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To delineate specific in vivo white matter pathology in neuronal intranuclear inclusion disease (NIID) using diffusion spectrum imaging (DSI) and define its clinical relevance. Methods DSI was performed on 42 NIID patients and 38 matched controls.
Kaiyan Jiang +10 more
wiley +1 more source