Abstract: Offloading machine learning models for network classification on high-throughput programmable switches is a promising technology, enabling line-speed in-network classification. Existing ...
Background: With optical coherence tomography (OCT), doctors are able to see cross-sections of the retinal layers and diagnose retinal diseases. Computer-aided diagnosis algorithms such as ...
Department of Chemistry and Chemical Engineering, Education and Research Center for Smart Energy and Materials, Inha University, Incheon 22212, Republic of Korea ...
Introduction: Human microbiota is a major factor contributing to the immune system, offering an opportunity to develop non-invasive methods for disease diagnosis. In some research on Autoimmune ...
U.S. tech giants are facing a reckoning from the East. Even as Nvidia pledged today to invest a staggering $100 billion into its own customer OpenAI's data centers — a move that raised eyebrows across ...
Trained a deep learning-based system using high-resolution Sentinel-2 imagery and CNNs to classify land into water, vegetation, urban and barren areas with 92.4% validation accuracy.
Abstract: In the field of medical image analysis, medical image classification is one of the most fundamental and critical tasks. Current researches often rely on the off-the-shelf backbone networks ...
Gemini’s mobile adoption has been soaring since the August launch of its Nano Banana image editor model, which has received positive reviews, particularly from users who say they can now more easily ...
This project implements a neural network from scratch to classify handwritten digits using the MNIST dataset. The neural network is built using Python and utilizes libraries such as NumPy and ...
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