Results 51 to 60 of about 11,738,094 (251)
Generative Adversarial Network (GAN) is an exciting innovation in machine learning within the neural network field. These models are able to generate a realistic image, video or even voice output.
Kališková Lenka, Butka Peter
doaj +1 more source
RandMixAugment: A Novel Unified Technique for Region- and Image-Level Data Augmentations
Deep learning models learn powerful representational spaces required for handling complex tasks. Recently, data augmentation techniques, region-level, and image-level augmentation have proved effective in significantly improving deep learning models ...
Yosoeb Shin +6 more
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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 +3 more
wiley +1 more source
A Data-Driven Approach to Classifying Wave Breaking in Infrared Imagery
We apply deep convolutional neural networks (CNNs) to estimate wave breaking type (e.g., non-breaking, spilling, plunging) from close-range monochrome infrared imagery of the surf zone.
Daniel Buscombe, Roxanne J. Carini
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Gastric cancer is a significant health concern, particularly in Korea, and its accurate detection is crucial for effective treatment. However, a gastroscopic biopsy can be time-consuming and may, thus, delay diagnosis and treatment.
Jae-beom Park +2 more
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We show that emergence of castration‐resistant prostate (CRPC) is associated with significant upregulation of cyclins that positively regulate cyclin‐dependent kinase 2 (CDK2) and concomitant downregulation of CDK4 cyclins. This renders CRPC cells dependent on the high activity of CDK2, and CDK2 inhibitors synergistically sensitize CRPC cells to both ...
Joyeeta Chatterjee +3 more
wiley +1 more source
The impact of the combination of image augmentation and feature augmentation operations.
The impact of the combination of image augmentation and feature augmentation operations.
Fan Wang (135182) +5 more
core +1 more source
Feature transforms for image data augmentation [PDF]
A problem with convolutional neural networks (CNNs) is that they require large datasets to obtain adequate robustness; on small datasets, they are prone to overfitting. Many methods have been proposed to overcome this shortcoming with CNNs.
Alessandra Lumini +3 more
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Image augmentation is a field that covers the subject area of altering existing data to create more for the use of model training processes. It may be seen as the practice of expanding upon existing data using a range of techniques that employ ...
Omer, Irfan, Lottering, Timothy
core +3 more sources
Evaluating GAN-Based Image Augmentation for Threat Detection in Large-Scale Xray Security Images
The inherent imbalance in the data distribution of X-ray security images is one of the most challenging aspects of computer vision algorithms applied in this domain.
Joanna Kazzandra Dumagpi, Yong-Jin Jeong
doaj +1 more source

