Results 61 to 70 of about 598,648 (280)

Spectral image data aggregation for multisource data augmentation

European Journal of Remote Sensing
Multispectral and hyperspectral images are increasingly popular in different research fields, such as remote sensing, astronomical imaging, or precision agriculture.
R. I. Luca, A. Baicoianu, I. C. Plajer
doaj   +1 more source

Dammarenediol II enhances etoposide‐induced apoptosis by targeting O‐GlcNAc transferase and Akt/GSK3β/mTOR signaling in liver cancer

Molecular Oncology, EarlyView.
Etoposide induces DNA damage, activating p53‐dependent apoptosis via caspase‐3/7, which cleaves PARP1. Dammarenediol II enhances this apoptotic pathway by suppressing O‐GlcNAc transferase activity, further decreasing O‐GlcNAcylation. The reduction in O‐GlcNAc levels boosts p53‐driven apoptosis and influences the Akt/GSK3β/mTOR signaling pathway ...
Jaehoon Lee, Byung‐Cheol Han, Gi‐Bang Koo, Jihye Park, Mijin Kwon, Young Bin Park, Jae‐Mun Choi, Seung‐Ho Lee, Sangho Roh   +8 more
wiley   +1 more source

Data augmentation scheme for federated learning with non-IID data

Tongxin xuebao, 2023
To solve the problem that the model accuracy remains low when the data are not independent and identically distributed (non-IID) across different clients in federated learning, a privacy-preserving data augmentation scheme was proposed.Firstly, a data ...
Lingtao TANG, Di WANG, Shengyun LIU
doaj   +2 more sources

Optimizing Rice Plant Disease Classification Using Data Augmentation with GANs on Convolutional Neural Networks

Intensif: Jurnal Ilmiah Penelitian Teknologi dan Penerapan Sistem Informasi
Background: Rice disease classification using CNN models faces challenges due to limited data, particularly in minority classes, and inconsistent image quality, which affect model performance.
Tinuk Agustin, Indrawan Ady Saputro, Mochammad Luthfi Rahmadi   +2 more
doaj   +1 more source

A New Multispectral Data Augmentation Technique Based on Data Imputation

Remote Sensing, 2021
Deep Learning (DL) has been recently introduced into the hyperspectral and multispectral image classification landscape. Despite the success of DL in the remote sensing field, DL models are computationally intensive due to the large number of parameters ...
Álvaro Acción, Francisco Argüello, Dora B. Heras   +2 more
doaj   +1 more source

TRAIL‐PEG‐Apt‐PLGA nanosystem as an aptamer‐targeted drug delivery system potential for triple‐negative breast cancer therapy using in vivo mouse model

Molecular Oncology, EarlyView.
Aptamers are used both therapeutically and as targeting agents in cancer treatment. We developed an aptamer‐targeted PLGA–TRAIL nanosystem that exhibited superior therapeutic efficacy in NOD/SCID breast cancer models. This nanosystem represents a novel biotechnological drug candidate for suppressing resistance development in breast cancer.
Gulen Melike Demirbolat, Aslihan Kucuk, Omer Erdogan, Samed Ozer, Bensu Kozan, Tugba Cuceli, Erkan Gumus, Evrim Cevik, Ozge Cevik   +8 more
wiley   +1 more source

SeisAug: A data augmentation python toolkit

Applied Computing and Geosciences
A common limitation in applying any deep learning and machine learning techniques is the limited labelled dataset which can be addressed through Data augmentation (DA). SeisAug is a DA python toolkit to address this challenge in seismological studies. DA.
D. Pragnath, G. Srijayanthi, Santosh Kumar, Sumer Chopra   +3 more
doaj   +1 more source

IMPDH inhibition enhances cytarabine efficacy in SAMHD1‐expressing leukaemia cells via guanine nucleotide depletion

Molecular Oncology, EarlyView.
Cytarabine is a key therapy for acute myeloid leukaemia (AML), but its efficacy is limited by the dNTPase SAMHD1, which hydrolyses its active metabolite. Screening nucleotide biosynthesis inhibitors revealed that IMPDH inhibitors selectively sensitise SAMHD1‐proficient AML cells to cytarabine.
Miriam Yagüe‐Capilla, Christopher Dirks, Caroline Eiden, Sonja K. Fesenmayer, Femke M. Hormann, Yolande Klootsema, Ingrid Lilienthal, Si Min Zhang, Nikolas Herold, Sean G. Rudd   +9 more
wiley   +1 more source

A survey on Image Data Augmentation for Deep Learning

Journal of Big Data, 2019
Deep convolutional neural networks have performed remarkably well on many Computer Vision tasks. However, these networks are heavily reliant on big data to avoid overfitting. Overfitting refers to the phenomenon when a network learns a function with very
Connor Shorten, Taghi M. Khoshgoftaar
doaj   +1 more source

Virtual data augmentation method for reaction prediction

Scientific Reports, 2022
To improve the performance of data-driven reaction prediction models, we propose an intelligent strategy for predicting reaction products using available data and increasing the sample size using fake data augmentation.
Xinyi Wu, Yun Zhang, Jiahui Yu, Chengyun Zhang, Haoran Qiao, Yejian Wu, Xinqiao Wang, Zhipeng Wu, Hongliang Duan   +8 more
doaj   +1 more source