IEEE

Intervention-Based Mixup Augmentation for Multiple Instance Learning in Whole-Slide Image Survival Analysis

Abstract: In the field of computational pathology, multiple instance learning (MIL) has become a critical modeling framework for analyzing gigapixel whole-slide images (WSIs). Data scarcity, ...
The Conversation

When fake data is a good thing – how synthetic data trains AI to solve real problems

Ambuj Tewari receives funding from NSF and NIH. You’ve just finished a strenuous hike to the top of a mountain. You’re exhausted but elated. The view of the city below is gorgeous, and you want to ...
Frontiers

Improving remote sensing scene classification with data augmentation techniques to mitigate class imbalance

1 Qingdao Huanghai University, Qingdao, China 2 College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao, China High-resolution remote sensing imagery is a powerful ...
The New York Times

OpenAI to Join Tech Giants in Building 5 New Data Centers in U.S.

Working with the Japanese conglomerate SoftBank and the cloud company Oracle, the A.I. start-up will spend $400 billion over the next five years. By Cade Metz Reporting from Abilene, Texas. A day ...
C&EN

Leveraging Deep Learning to Address Diagnostic Challenges with Insufficient Image Data

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. In recent AI-driven disease diagnosis, the success of models has depended mainly on ...
Scientific Research Publishing

Frid-Adar, M., Diamant, I., Klang, E., Amitai, M., Goldberger, J. and Greenspan, H. (2018) GAN-Based Synthetic Medical Image Augmentation for Increased CNN Performance in Liver ...

ABSTRACT: High-quality data is essential for hospitals, public health agencies, and governments to improve services, train AI models, and boost efficiency. However, real data comes with challenges: ...
Frontiers

Enhancing buckwheat maturity classification with generative adversarial networks for spectroscopy data augmentation

Introduction: The optimal harvest period for buckwheat is challenging to determine due to its short growth cycle. Harvesting too early or too late can negatively affect the quality of the crop.
IEEE

Research on data augmentation for image classification based on convolution neural networks

Abstract: The performance of deep convolution neural networks will be further enhanced with the expansion of the training data set. For the image classification tasks, it is necessary to expand the ...