Comparison of feature representations in MRI-based MCI-to-AD conversion prediction.
Sign Up to like & getrecommendations! Published in 2018 at "Magnetic resonance imaging"
DOI: 10.1016/j.mri.2018.03.003
Abstract: Alzheimer's disease (AD) is a progressive neurological disorder in which the death of brain cells causes memory loss and cognitive decline. The identification of at-risk subjects yet showing no dementia symptoms but who will later… read more here.
Keywords: feature representations; conversion prediction; performance; conversion ... See more keywords
Enzyme Substrate Prediction from Three-Dimensional Feature Representations Using Space-Filling Curves
Sign Up to like & getrecommendations! Published in 2023 at "Journal of chemical information and modeling"
DOI: 10.1021/acs.jcim.3c00005
Abstract: Compact and interpretable structural feature representations are required for accurately predicting properties and function of proteins. In this work, we construct and evaluate three-dimensional feature representations of protein structures based on space-filling curves (SFCs). We… read more here.
Keywords: three dimensional; feature representations; space filling; filling curves ... See more keywords
Federated Learning via Attentive Margin of Semantic Feature Representations
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2022.3209865
Abstract: Federated learning (FL) in Internet of Things (IoT) systems enables distributed model training using a large corpus of decentralized training data dispersed among multiple IoT clients. In this distributed setting, system and statistical heterogeneity, in… read more here.
Keywords: federated learning; representations learned; via attentive; margin ... See more keywords
Teaching Teachers First and Then Student: Hierarchical Distillation to Improve Long-Tailed Object Recognition in Aerial Images
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2022.3177853
Abstract: Remote sensing data distribution generally exposes the long-tail characteristic. This will limit the object recognition performance of existing deep models when they are trained with such unbalanced data. In this paper, we propose a novel… read more here.
Keywords: distillation; feature representations; object recognition; student ... See more keywords
Vector-Based Feature Representations for Speech Signals: From Supervector to Latent Vector
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Multimedia"
DOI: 10.1109/tmm.2020.3014559
Abstract: There are two basic types of feature representations for speech signals. The first type refers to probabilistic models, such as the Gaussian mixture model (GMM). The second type refers to vector-based feature representations, such as… read more here.
Keywords: vector; feature representations; vector based; representations speech ... See more keywords