Results 81 to 90 of about 599,022 (331)

Gibbs Max-margin Topic Models with Data Augmentation [PDF]

, 2013
Max-margin learning is a powerful approach to building classifiers and structured output predictors. Recent work on max-margin supervised topic models has successfully integrated it with Bayesian topic models to discover discriminative latent semantic ...
Chen, Ning, Perkins, Hugh, Zhang, Bo, Zhu, Jun   +3 more
core  

Natural Products as Geroprotective Modulators in Diabetic Nephropathy: A Mechanistic Framework Integrating Aging Hallmarks and the AMPK–SIRT1–Nrf2 Axis

Aging and Cancer, EarlyView.
Natural products target the aging kidney in diabetic nephropathy by restoring the AMPK–SIRT1–Nrf2 axis, reducing oxidative stress, inflammation, fibrosis, and cellular senescence while enhancing mitochondrial biogenesis and antioxidant defenses.
Sherif Hamidu, Latif Adams, Eunice Ampem‐Danso, Justice Kumi, Abigail Aning, Fatima Hamidu, Mustapha Abdul Mumin Mohammed, Ayuba Nii Darku Ankrah, Seth Kwabena Amponsah   +8 more
wiley   +1 more source

What is The Best Data Augmentation For 3D Brain Tumor Segmentation? [PDF]

, 2021
Marco Domenico Cirillo, David Abramian, Anders Eklund   +2 more
openalex   +1 more source

NR4A1 Exerts Pro‐Tumor Role in Glioblastoma via Inducing xCT/GPX4‐Regulated Ferroptosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Purpose This study investigates NR4A1's paradoxical roles in glioblastoma (GBM) progression, focusing on its mechanistic link to ferroptosis regulation. We aimed to resolve conflicting reports of NR4A1 as both an oncogene and a tumor suppressor by defining its transcriptional control over xCT/GPX4‐mediated iron homeostasis and its clinical ...
Peng Tao, Shikuan Din, Zhengkang Fu, Qian Sun, Xiwei Zhu, Yuxin Wei, Huan Qu, Xinyi Zhang, Jiaxuan Liu, Chuhua Fu, Qianxue Chen   +10 more
wiley   +1 more source

Data Augmentation-Based Photovoltaic Power Prediction

Energies
In recent years, as the grid-connected installed capacity of photovoltaic (PV) power generation has increased by leaps and bounds, it has assumed considerable importance in predicting PV power output.
Xifeng Wang, Yijun Shen, Haiyu Song, Shichao Liu   +3 more
doaj   +1 more source

Survey of Image Data Augmentation Techniques Based on Deep Learning [PDF]

Jisuanji kexue
In recent years,deep learning has demonstrated excellent performance in many computer vision tasks such as image classification,object detection,and image segmentation.Deep neural networks usually rely on a large amount of training data to avoid ...
SUN Shukui, FAN Jing, SUN Zhongqing, QU Jinshuai, DAI Tingting
doaj   +1 more source

Rethinking data augmentation for adversarial robustness [PDF]

, 2023
Hamid Eghbal-zadeh, Werner Zellinger, Maura Pintor, Kathrin Grosse, Khaled Koutini, Bernhard Moser, Battista Biggio, Gerhard Widmer   +7 more
openalex   +1 more source

Differentiable automatic data augmentation

, 2020
Data augmentation (DA) techniques aim to increase data variability, and thus train deep networks with better generalisation. The pioneering AutoAugment automated the search for optimal DA policies with reinforcement learning. However, AutoAugment is extremely computationally expensive, limiting its wide applicability.
Li, Yonggang, Hu, Guosheng, Wang, Yongtao, Hospedales, Timothy, Robertson, Neil M, Yang, Yongxin   +5 more
openaire   +2 more sources

Tied-Augment: Controlling Representation Similarity Improves Data Augmentation

, 2023
14 pages, 2 figures, ICML ...
Kurtulus, Emirhan, Li, Zichao, Dauphin, Yann, Cubuk, Ekin Dogus   +3 more
openaire   +2 more sources

Diffusion Tractography Biomarker for Epilepsy Severity in Children With Drug‐Resistant Epilepsy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To develop a novel deep‐learning model of clinical DWI tractography that can accurately predict the general assessment of epilepsy severity (GASE) in pediatric drug‐resistant epilepsy (DRE) and test if it can screen diverse neurocognitive impairments identified through neuropsychological assessments.
Jeong‐Won Jeong, Min‐Hee Lee, Hiroshi Uda, Yoon Ho Hwang, Michael Behen, Aimee Luat, Csaba Juhász, Eishi Asano   +7 more
wiley   +1 more source