Results 61 to 70 of about 1,979,450 (271)
Partial Transfer Learning with Selective Adversarial Networks
, 2017 Adversarial learning has been successfully embedded into deep networks to learn transferable features, which reduce distribution discrepancy between the source and target domains.
Cao, Zhangjie +3 more
core +1 more source
FEBS Open Bio, EarlyView.Bioscience students were asked for their opinions on the value and teaching of skills. 204 responded that teamwork, time management and study skills are necessary to reach University, that scientific writing, research, laboratory and presentation skills are taught effectively during their studies, while other skills are gained inherently through study ...
Janella Borrell, Susan Crennell
wiley +1 more source
TRANSFER LEARNING APPROACH FOR CLASSIFICATION OF WIDELY USED SPICES
Yanbu Journal of Engineering and Science, 2022 People around the world relish variety of food that are flavourful. Spices add flavours to the food without adding any fat or calories. People have used spices for many centuries and are an integral part of our food.
Arunachalam Sundaram +3 more
doaj
Learning to Selectively Transfer [PDF]
Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining, 2019 Accepted to WSDM ...
Qu, Chen +7 more
openaire +2 more sources
Aging and Cancer, EarlyView.This systematic review synthesizes prognostic models for survival and recurrence in resected non‐small cell lung cancer. While many models demonstrate moderate to good discrimination, few are externally validated and reporting quality is variable, limiting clinical applicability and highlighting the need for robust, transparent model development ...
Evangeline Samuel +4 more
wiley +1 more source
Structure transfer and consolidation in visual implicit learning
eLifeTransfer learning, the re-application of previously learned higher-level regularities to novel input, is a key challenge in cognition. While previous empirical studies investigated human transfer learning in supervised or reinforcement learning for ...
Dominik Garber, József Fiser
doaj +1 more source
CNN Ensemble learning method for Transfer learning: A Review
Ilkom Jurnal Ilmiah, 2023 This study provides a review of CNN's ensemble learning method for transfer learning by highlighting sections such as review studies, datasets, pre-trained models, transfer learning, ensemble learning, and performance.
Yudha Islami Sulistya +2 more
doaj +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Super‐Refractory Status Epilepticus (SRSE) is a rare, life‐threatening neurological emergency with unclear etiology in many cases. Mitochondrial dysfunction, often due to disease‐causing genetic variants, is increasingly recognized as a cause, with each gene producing distinct pathophysiological mechanisms.
Pouria Mohammadi +2 more
wiley +1 more source
Knowledge-based Transfer Learning Explanation [PDF]
, 2018 Machine learning explanation can significantly boost machine learning's application in decision making, but the usability of current methods is limited in human-centric explanation, especially for transfer learning, an important machine learning branch ...
Chen, Huajun +4 more
core +2 more sources
Clustering Algorithm Reveals Dopamine‐Motor Mismatch in Cognitively Preserved Parkinson's Disease
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To explore the relationship between dopaminergic denervation and motor impairment in two de novo Parkinson's disease (PD) cohorts. Methods n = 249 PD patients from Parkinson's Progression Markers Initiative (PPMI) and n = 84 from an external clinical cohort.
Rachele Malito +14 more
wiley +1 more source