This tutorials is part of a three-part series: * `NLP From Scratch: Classifying Names with a Character-Level RNN <https://pytorch.org/tutorials/intermediate/char_rnn ...

This jupyter notebook tutorial is meant to be a general introduction to machine and deep learning. We use seismic time series data from i) real earthquakes and ii) nuisance signals to train a suite of ...

At a number of area schools, multi-age classes combine students from different grades into one class. Staff members said this allows students to have the same teachers and classrooms for a few years, ...

In this tutorial, we build a robust, multi-layered safety filter designed to defend large language models against adaptive and paraphrased attacks. We combine semantic similarity analysis, rule-based ...

Abstract: Multi-class classification is a current research area within machine learning, aimed at solving problems where input data is categorized into more than two classes. The dataset is in English ...

This paper introduces an Ultra-Lightweight Uncertainty-Aware Ensemble (UALE) model for large-scale multi-class medical MRI diagnosis, evaluated on the 2024 Benchmark Diagnostic MRI and Medical Imaging ...

Lockheed Martin Skunk Works® and XTEND have expanded their collaboration to support joint all-domain command and control (JADC2) missions. The companies integrated the XTEND Operating System (XOS) ...

Abstract: The present study introduces FPGA(Field-Programmable Gate Array)-based Real-Time Multi-Class Vehicle Classification using Millimeter wave Radar (mmWave radar), which overcomes the ...

Colorectal cancer is the third most common cancer worldwide, and accurate pathological diagnosis is crucial for clinical intervention and prognosis assessment. Although deep learning has shown promise ...