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 ...

thanks for providing this soft, I would love to test it, but I can not figure out what is the problem I run the run_shiva.py with python run_shiva.py --in /input_path_ok/ --sub_names suj1 --out ...

The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...

Abstract: Robotics research encompasses a wide range of technical challenges and interdisciplinary approaches. This study introduces a dual-paradigm classification framework for organizing the stated ...

Too Long; Didn't Read This tutorial walks you through fine-tuning a ResNet-18 model from TensorFlow’s Model Garden for classifying images in the CIFAR-10 dataset. You’ll learn how to set up the ...

ABSTRACT: Accurate prediction of malaria incidence is indispensable in helping policy makers and decision makers intervene before the onset of an outbreak and potentially save lives. Various ...

Abstract: We consider a human-automation team jointly solving binary classification tasks over multiple time stages. At each stage, the automation observes the data for a batch of classification tasks ...

ABSTRACT: The advent of the internet, as we all know, has brought about a significant change in human interaction and business operations around the world; yet, this evolution has also been marked by ...

The advancement of large language models (LLMs) has significantly influenced interactive technologies, presenting both benefits and challenges. One prominent issue arising from these models is their ...