I found two interesting automotive SoCs in the Linux 6.19 changelog: Renesas R-Car X5H 16-/32-core Cortex-A720AE SoC and ...
The original version of this story appeared in Quanta Magazine. If you want to solve a tricky problem, it often helps to get organized. You might, for example, break the problem into pieces and tackle ...
Deep Learning for High-Dimensional Sense, Non-Linear Signal Processing and Intelligent Diagnosis, vol II ...
Epilepsy detection using artificial intelligence (AI) networks has gained significant attention. However, existing methods face challenges in accuracy, computational cost, and speed. CNN excel in ...
Abstract: The quantitative evaluation of defects is one of the challenges of eddy current (EC) testing. Efficient algorithm that requires a small amount of time and hardware resources is needed. In ...
Abstract: In recent years, FPGA-based convolutional neural networks (CNNs) accelerator has received tremendous research interest, especially in fields such as autonomous driving and robotics. For the ...
In tackling the intricate task of predicting brain age, researchers introduce a groundbreaking hybrid deep learning model that integrates Convolutional Neural Networks (CNN) and Multilayer Perceptron ...
error in inference process (no valid convolution algorithms available in CuDNN) #25 ...
ABSTRACT: Spam emails pose a threat to individuals. The proliferation of spam emails daily has rendered traditional machine learning and deep learning methods for screening them ineffective and ...
Reasoning efficiently across extended sequences is a major difficulty in machine learning. Recently, convolutions have emerged as a critical primitive for sequence modeling, supporting ...
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