A new technical paper titled “Hardware-software co-exploration with racetrack memory based in-memory computing for CNN inference in embedded systems” was published by researchers at National ...

While artificial intelligence (AI) holds promise to improve the diagnosis of melanoma, researchers of a new review outlined ...

In today’s digital age, Convolutional Neural Networks (CNNs), a subset of Deep Learning (DL), are widely used for various computer vision tasks such as image classification, object detection, and ...

Applied Analytics professor Siddhartha Dalal discusses the impacts of applied technologies on real-life risk management.

Nonpoint source pollution, characterized by its diffuse origins and transport mechanisms, remains a central barrier to global ...

In this paper, Object Detection and Tracking System (ODTS) in combination with a well-known deep learning network, Faster Regional Convolution Neural Network (Faster R-CNN), for Object Detection and ...

The study found that deep learning models, especially CNNs, were the most frequently implemented technique (61.2%), followed ...

Through the course, participants will learn about Python, machine learning models, data processing, and interpretation, with a focus on practical use.

We explore propagation of seismic interpretation by deep learning in stacked 2D sections. We show the application of state-of-the-art image classification algorithms on seismic data. These algorithms ...