Sex classification from functional brain connectivity: Generalization to multiple datasets
Sign Up to like & getrecommendations! Published in 2024 at "Human Brain Mapping"
DOI: 10.1002/hbm.26683
Abstract: Machine learning (ML) approaches are increasingly being applied to neuroimaging data. Studies in neuroscience typically have to rely on a limited set of training data which may impair the generalizability of ML models. However, it… read more here.
Keywords: sex classification; generalization performance; training; generalization ... See more keywords
Radiomics feature analysis and model research for predicting histopathological subtypes of non-small cell lung cancer on CT images: a multi-dataset study.
Sign Up to like & getrecommendations! Published in 2023 at "Medical physics"
DOI: 10.1002/mp.16233
Abstract: PURPOSE Classifying the subtypes of non-small cell lung cancer (NSCLC) is essential for clinically adopting optimal treatment strategies and improving clinical outcomes, but the histological subtypes are confirmed by invasive biopsy or post-operative examination at… read more here.
Keywords: cell; study; generalization performance; cancer ... See more keywords
Examining generalization performance in a conditional discrimination task for learners with moderate-to-severe intellectual and developmental disabilities: Using a generalization gradient
Sign Up to like & getrecommendations! Published in 2018 at "European Journal of Behavior Analysis"
DOI: 10.1080/15021149.2018.1507073
Abstract: ABSTRACT This study examined how differences between teaching stimuli in a conditional discrimination impacted discrimination/generalization outcomes among learners with intellectual and developmental disabilities (IDD). In Study 1, three color sets were identified among 30 typically… read more here.
Keywords: generalization; generalization performance; conditional discrimination; discrimination ... See more keywords
Improving generalization performance of electrocardiogram classification models
Sign Up to like & getrecommendations! Published in 2023 at "Physiological Measurement"
DOI: 10.1088/1361-6579/acb30f
Abstract: Objective. Recently, many electrocardiogram (ECG) classification algorithms using deep learning have been proposed. Because the ECG characteristics vary across datasets owing to variations in factors such as recorded hospitals and the race of participants, the… read more here.
Keywords: generalization performance; classification; model; challenge ... See more keywords
Evaluation and Improvement of Generalization Performance of SAR Ship Recognition Algorithms
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2022.3216623
Abstract: As artificial intelligence continues to advance, deep learning has greatly contributed to the advancement of ship recognition using synthetic aperture radar (SAR) images. Deep learning-based SAR ship recognition performance is largely dependent on the sample… read more here.
Keywords: recognition; generalization performance; sar ship; ship recognition ... See more keywords
Efficient Classification by Removing Bayesian Confusing Samples
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Knowledge and Data Engineering"
DOI: 10.1109/tkde.2023.3303425
Abstract: Improving the generalization performance of classifiers from data pre-processing perspective has recently received considerable attention in the machine learning community. Although many methods have been proposed in the past decades, most of them lack theoretical… read more here.
Keywords: generalization performance; removing bayesian; confusing samples; bayesian confusing ... See more keywords
Towards Better Generalization of Deep Neural Networks via Non-Typicality Sampling Scheme.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2022.3147031
Abstract: Improving the generalization performance of deep neural networks (DNNs) trained by minibatch stochastic gradient descent (SGD) has raised lots of concerns from deep learning practitioners. The standard simple random sampling (SRS) scheme used in minibatch… read more here.
Keywords: neural networks; sampling scheme; generalization performance; deep neural ... See more keywords