Abstract: Recently, there has been a proliferation of applied machine learning (ML) research, including the use of convolutional neural networks (CNNs) for direction of arrival (DoA) estimation. With ...
This project implements ResNet-50, a deep convolutional neural network with 50 layers that uses residual connections to enable training of very deep networks. The architecture includes identity ...
To explain how a convolutional neural network (CNN) processes an image, it is common to generate classification activation maps (CAMs) to reveal image areas that are relevant to output. Nevertheless, ...
Extreme Networks has fully launched its Extreme Platform One, an agentic AI-focused network visualization offering. Revealed back in February, the platform is now generally available, with the vendor ...
Retinal diseases are among the leading causes of blindness worldwide, requiring early detection for effective treatment. Manual interpretation of ophthalmic imaging, such as optical coherence ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Raman spectroscopy in biological applications faces challenges due to complex spectra, ...
Physics-informed neural networks were tested for their capabilities in predicting concentration profiles in gradient liquid chromatography. Rzeszow University of Technology researchers based in ...
In this series of articles, I am looking at how to monitor my home/home lab LAN. In my first article, I probed my network to see what devices were on it and where they were located. In my next article ...
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