Abstract: FPGAs provide customizable, low-power, and real-time ML Models acceleration for embedded systems, making them ideal for edge applications like robotics and IoT. However, ML models are ...

A Scorpio Tankers vessel making its debut in the US government’s Tanker Security Program (TSP) is replacing a Stena ship that was damaged in a fiery North Sea collision in March. Scorpio’s 50,000-dwt ...

The threat actor behind the malware-as-a-service (MaaS) framework and loader called CastleLoader has also developed a remote access trojan known as CastleRAT. "Available in both Python and C variants, ...

Before conducting the experiment, participants attended a training session. In this session, the details of the experiment were explained for the participants, and several items were presented to them ...

BETA TESTERS WANTED! VAP is a computational engine that uses both CPU and GPU (if available) to do mass amounts of arithmetic operations. Also comes with its own API! I built a terminal-based ...

Here is the easy math that solves the most significant business problem of them all: how to optimize millions of operational decisions. Deep down, we all know that we should embrace difficulties ...

MEXICO CITY, Jan 29 (Reuters) - Mexico President Claudia Sheinbaum said that her government will send Congress on Wednesday a bill intended to reform the country's energy sectors and establish ...

In 2024 organizations informed the US government about 720 healthcare data breaches affecting a total of 186 million user records. In 2024, organizations informed the US government about more than 700 ...

Operator learning is a transformative approach in scientific computing. It focuses on developing models that map functions to other functions, an essential aspect of solving partial differential ...

A calculator that uses handwritten Kannada digits and operators to calculate the result, using contour detection and CNN model predictions. Made using PyTorch, OpenCV, PIL and CustomTkinter. A ...

Abstract: Approximate computing (AxC) is being widely researched as a viable approach to deploying compute-intensive artificial intelligence (AI) applications on resource-constrained embedded systems.