Results 81 to 90 of about 693,698 (310)
Optics ExpressModern photon-counting sensors are increasingly dominated by Poisson noise, yet conventional feature-specific imaging (FSI), based on principal component analysis (PCA), is optimized for additive Gaussian noise and variance preservation rather than task-specific objectives, leading to suboptimal performance and a loss of its advantages under Poisson ...
Yizhou Lu, Andreas Velten
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FEBS Letters, EarlyView.We identified a systemic, progressive loss of protein S‐glutathionylation—detected by nonreducing western blotting—alongside dysregulation of glutathione‐cycle enzymes in both neuronal and peripheral tissues of Taiwanese SMA mice. These alterations were partially rescued by SMN antisense oligonucleotide therapy, revealing persistent redox imbalance as ...
Sofia Vrettou, Brunhilde Wirth
wiley +1 more source
The spatial domain image and its deep features.
, 2018 The spatial domain image and its deep features.
Zhizheng Liang (4994216) +3 more
core +1 more source
Journal of ImagingThe increasing use of high-resolution cross-sectional imaging has significantly enhanced the detection of pancreatic cystic lesions (PCLs), including pseudocysts and neoplastic entities such as IPMN, MCN, and SCN. However, accurate categorization of PCLs
Neus Torra-Ferrer +11 more
doaj +1 more source
Frontiers in Oncology, 2023 Skin cancer is a serious disease that affects people all over the world. Melanoma is an aggressive form of skin cancer, and early detection can significantly reduce human mortality. In the United States, approximately 97,610 new cases of melanoma will be
Naveed Ahmad +8 more
doaj +1 more source
Deep Feature Deformation Weights
CoRRProject page at https://threedle.github.io ...
Richard Liu, Itai Lang, Rana Hanocka
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Hybrid Models with Deep and Invertible Features
CoRR, 2019 We propose a neural hybrid model consisting of a linear model defined on a set of features computed by a deep, invertible transformation (i.e. a normalizing flow). An attractive property of our model is that both p(features), the density of the features, and p(targets | features), the predictive distribution, can be computed exactly in a single feed ...
Eric, N +4 more
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Deep-FS: A feature selection algorithm for Deep Boltzmann Machines [PDF]
Neurocomputing, 2018 A Deep Boltzmann Machine is a model of a Deep Neural Network formed from multiple layers of neurons with nonlinear activation functions. The structure of a Deep Boltzmann Machine enables it to learn very complex relationships between features and facilitates advanced performance in learning of high-level representation of features, compared to ...
Taherkhani, A, Cosma, G, McGinnity, TM
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FEBS Letters, EarlyView.In this study, we found that human cervical‐derived adipocytes maintain intracellular iron level by regulating the expression of iron transport‐related proteins during adrenergic stimulation. Melanotransferrin is predicted to interact with transferrin receptor 1 based on in silico analysis.
Rahaf Alrifai +9 more
wiley +1 more source
The intermediate-frequency representation of image and its deep features.
, 2018 The intermediate-frequency representation of image and its deep features.
Zhizheng Liang (4994216) +3 more
core +1 more source