Results 51 to 60 of about 28,763 (261)

Active Instance Selection for Few-Shot Classification

IEEE Access, 2022
Few-shot learning aims to develop well-trained models by using only a few annotated samples. However, the performance of few-shot learning deteriorates if inappropriate support samples are selected.
Junsup Shin, Youngwook Kang, Seungjin Jung, Jongwon Choi   +3 more
doaj   +1 more source

Value of MRI Outcomes for Preventive and Early‐Stage Trials in Spinocerebellar Ataxias 1 and 3

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To examine the value of MRI outcomes as endpoints for preventive and early‐stage trials of two polyglutamine spinocerebellar ataxias (SCAs). Methods A cohort of 100 participants (23 SCA1, 63 SCA3, median Scale for the Assessment and Rating of Ataxia (SARA) score = 5, 42% preataxic, and 14 gene‐negative controls) was scanned at 3T up ...
Thiago J. R. Rezende, Emilien Petit, Young Woo Park, Sophie Tezenas du Montcel, James M. Joers, Jonathan M. DuBois, H. Moore Arnold, Michal Povazan, Ipek Özdemir, Guita Banan, Romain Valabregue, Philipp Ehses, Jennifer Faber, Chiadi U. Onyike, Peter B. Barker, Jeremy D. Schmahmann, Eva‐Maria Ratai, Sub H. Subramony, Thomas H. Mareci, Khalaf O. Bushara, Henry Paulson, Thomas Klockgether, Alexandra Durr, Tetsuo Ashizawa, Christophe Lenglet, Gülin Öz, READISCA Investigators   +26 more
wiley   +1 more source

A New Instrument Monitoring Method Based on Few-Shot Learning

Applied Sciences, 2023
As an important part of the industrialization process, fully automated instrument monitoring and identification are experiencing an increasingly wide range of applications in industrial production, autonomous driving, and medical experimentation. However,
Beini Zhang, Liping Li, Yetao Lyu, Shuguang Chen, Lin Xu, Guanhua Chen   +5 more
doaj   +1 more source

Screening Routine Clinical Notes for Epilepsy Surgery Candidates Using Large Language Models

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Epilepsy surgery is severely underutilized despite proven efficacy, with substantial under‐referral of eligible patients in routine clinical practice. This study evaluated the potential role of large language models (LLMs) as decision‐support tools for screening unstructured clinical notes to identify epilepsy surgery candidates and ...
Uriel Fennig, Nadav Amir, Maya Schiller, Roni Loebenstein, Johnatan Nissan, Marina Boxer, Shany Guly Gofrit, Gal Goshen, Sándor Beniczky, Nicola Maggio   +9 more
wiley   +1 more source

Hybrid attentive prototypical network for few-shot action recognition

Complex & Intelligent Systems
Most previous few-shot action recognition works tend to process video temporal and spatial features separately, resulting in insufficient extraction of comprehensive features.
Zanxi Ruan, Yingmei Wei, Yanming Guo, Yuxiang Xie   +3 more
doaj   +1 more source

Plain Template Insertion: Korean-Prompt-Based Engineering for Few-Shot Learners

IEEE Access, 2022
Prompt-based learning is a method used for language models to interpret natural language by remembering the prior knowledge acquired and the training objective.
Jaehyung Seo, Hyeonseok Moon, Chanhee Lee, Sugyeong Eo, Chanjun Park, Jihoon Kim, Changwoo Chun, Heuiseok Lim   +7 more
doaj   +1 more source

From Few-Shot Optimal Control to Few-Shot Learning

CoRR
6 ...
Roman A. Chertovskih, Nikolay Pogodaev, Maxim V. Staritsyn, A. Pedro Aguiar   +3 more
openaire   +2 more sources

Meta-Transfer Learning for Few-Shot Learning

2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019
CVPR ...
Qianru Sun, Yaoyao Liu 0001, Tat-Seng Chua, Bernt Schiele   +3 more
openaire   +5 more sources

Prototype Completion for Few-Shot Learning

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023
Few-shot learning aims to recognize novel classes with few examples. Pre-training based methods effectively tackle the problem by pre-training a feature extractor and then fine-tuning it through the nearest centroid based meta-learning. However, results show that the fine-tuning step makes marginal improvements.
Baoquan Zhang, Xutao Li 0003, Yunming Ye, Shanshan Feng 0001   +3 more
openaire   +3 more sources

A 17 Year Old With Developmental Delay Presenting With Increasing Confusion and Imbalance

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Methylmalonic acidemia is an autosomal recessive genetic disorder primarily caused by defects in methylmalonyl‐CoA mutase and cobalamin (vitamin B12) metabolism. These defects disrupt the tricarboxylic acid cycle and oxidative phosphorylation, leading to the abnormal accumulation of metabolic products such as methylmalonic acid, propionic acid,
Wei Zhao, Yingli Zhang, Hongliang Zheng
wiley   +1 more source