Results 71 to 80 of about 252,636 (309)

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

Stimulator of interferon genes agonist augmented antitumor immunity of osimertinib in Egfr‐mutated lung cancer

Molecular Oncology, EarlyView.
Combining osimertinib with the STING agonist ADU‐S100 activates innate and adaptive immunity to overcome the non‐inflamed microenvironment of Egfr‐mutant lung cancer. This combination increases NK and CD8+ T‐cell infiltration, associated with activation of the STING‐IRF3 pathway and local immunogenic cell death.
Jun Nishimura, Tadahiro Kuribayashi, Johannes Brägelmann, Sachi Okawa, Masataka Taoka, Shunta Mori, Tomoka Nishimura, Takaaki Tanaka, Go Makimoto, Kiichiro Ninomiya, Kammei Rai, Eiki Ichihara, Ryohei Katayama, Katsuyuki Hotta, Masahiro Tabata, Yosuke Togashi, Yoshinobu Maeda, Martin L. Sos, Katsuyuki Kiura, Kadoaki Ohashi   +19 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

Counterexample-Guided Data Augmentation [PDF]

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018
We present a novel framework for augmenting data sets for machine learning based on counterexamples. Counterexamples are misclassified examples that have important properties for retraining and improving the model. Key components of our framework include a \textit{counterexample generator}, which produces data items that are misclassified by the ...
Dreossi, Tommaso, Ghosh, Shromona, Yue, Xiangyu, Keutzer, Kurt, Sangiovanni-Vincentelli, Alberto, Seshia, Sanjit A   +5 more
openaire   +5 more sources

A novel quinazolinone insulin receptor inhibitor and its synergy with an EGFR inhibitor in glucose‐driven glioblastoma

Molecular Oncology, EarlyView.
The novel styrylquinazolinone‐based molecule W1B effectively suppresses glioblastoma by inhibiting IGF1R and EGFR. In high‐glucose microenvironments driving tumor resistance, W1B acts synergistically with the EGFR inhibitor dacomitinib. This combination safely blocks compensatory survival signaling in zebrafish xenograft models. Showcasing promising in
Patryk Rurka, Wioleta Cieślik, Wojciech Płaziński, Katarzyna Stępnik, Anna Boguszewska‐Czubara, Elżbieta Kot, Robert Musioł, Mateusz Jasica, Anna Mrozek‐Wilczkiewicz, Katarzyna Malarz   +9 more
wiley   +1 more source

The Data Augmentation Algorithm

The data augmentation (DA) algorithms are popular Markov chain Monte Carlo (MCMC) algorithms often used for sampling from intractable probability distributions. This review article comprehensively surveys DA MCMC algorithms, highlighting their theoretical foundations, methodological implementations, and diverse applications in frequentist and Bayesian ...
Roy, Vivekananda, Khare, Kshitij, Hobert, James P.   +2 more
openaire   +2 more sources

Epigenetic heterogeneity and plasticity in therapy‐induced tumor states through single‐cell multi‐omics

Molecular Oncology, EarlyView.
Single‐cell multi‐omics reveals epigenetic heterogeneity across therapy‐adaptive tumor states, including quiescent/dormant, drug‐tolerant persister, and EMT‐like phenotypes. By linking regulatory features with state‐associated biomarkers, these approaches inform biomarker‐guided therapeutic strategies for evolving tumors.
Hee Jung Kim, Hwiyeong Lee, Jin Hong, Daechan Park   +3 more
wiley   +1 more source

Data augmentation strategies to improve reaction yield predictions and estimate uncertainty

, 2020
Chemical reactions describe how precursor molecules react together and transform into products. The reaction yield describes the percentage of the precursors successfully transformed into products relative to the theoretical maximum.
Alain C., Vaucher, Jean-Louis, Reymond, Teodoro, Laino, Philippe, Schwaller   +3 more
core   +1 more source

Comparison of Different Image Data Augmentation Approaches

Journal of Imaging, 2021
Convolutional neural networks (CNNs) have gained prominence in the research literature on image classification over the last decade. One shortcoming of CNNs, however, is their lack of generalizability and tendency to overfit when presented with small ...
Loris Nanni, Michelangelo Paci, Sheryl Brahnam, Alessandra Lumini   +3 more
doaj   +1 more source