AI success depends on whether enterprise data is ready, reachable, and close enough to the workloads that need it. In this eSpeaks episode, Dell Technologies’ Vrashank Jain explains why fragmented ...

Recently, in a lecture room at the Daegu Startup Hub in Dong-gu, Daegu, Kim Soo-pil, a senior researcher at the Daegu ...

A 1958 invention, the Perceptron, revolutionized computing by enabling machines to learn from experience, not just ...

Abstract: Deep learning (DL) methods and architectures have been the state-of-the-art classification algorithms for computer vision and natural language processing problems. However, the successful ...

Accurate RNA splicing is essential for gene expression and human health, yet predicting how DNA sequence variations affect ...

Explore how AI phenotypic screening transforms image-based drug discovery through advanced phenotypic data analysis and ML-driven cell-based assays.

Recent advances in the field of medical imaging and computational neuroscience have transformed the landscape of brain pathology detection. The application of deep learning and artificial intelligence ...

Abstract: We propose a novel spatiotemporal fusion method based on deep convolutional neural networks (CNNs) under the application background of massive remote sensing data. In the training stage, we ...

Over 70 million people in the U.S. are impacted by hearing loss, and age-related hearing loss is the second most common ...

This GitHub Repository was produced to share material relevant to the Journal paper Automatic crack classification and segmentation on masonry surfaces using convolutional neural networks and transfer ...

Endoscopy-based deep learning algorithms achieve higher sensitivity, specificity, and overall diagnostic accuracy than endoscopists for early ESCC detection.

From detecting pancreatic cancer three years early to recognising 18 tumour types from a handful of tissue slides, AI is transforming medicine. Here is a comprehensive guide to the breakthroughs, the ...