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Abstract: A robust approach for brain tumor classification is being developed using deep convolutional neural networks (CNNs). This study leverages an open-source dataset derived from the MRI ...

Abstract: Feature selection in a traditional binary classification algorithm is always used in the stage of dataset preprocessing, which makes the obtained features not necessarily the best ones for ...

conda create -n unifolm-wma python==3.10.18 conda activate unifolm-wma conda install pinocchio=3.2.0 -c conda-forge -y conda install ffmpeg=7.1.1 -c conda-forge git ...

This paper introduces a novel benchmark dataset designed to support fairness-oriented research in artificial intelligence within the educational domain. The dataset originates from longitudinal survey ...

This data descriptor presents novel, annotated 3D point cloud plant scans generated by a high-throughput phenotyping platform (LeasyScan, ICRISAT, India). It focuses on broad-leaf legume species ...

A new technical paper titled “VerilogDB: The Largest, Highest-Quality Dataset with a Preprocessing Framework for LLM-based RTL Generation” was published by researchers at the University of Florida.

The phenomenon, in which travelers choose vacation destinations based on beloved, sometimes dark, TV series and films, has become one of the biggest trends in travel. By Danial Adkison This article is ...

When it comes to machine learning and artificial intelligence, the common misconception is that the choice of model determines the success of a project. While models play a crucial role, the quality ...

Data preprocessing is an essential phase in the machine learning workflow, as it prepares raw data for model training. Without proper preprocessing, the model's performance can be significantly ...

End-to-end customer churn analysis with EDA, ML prediction (XGBoost, Random Forest), and interactive React dashboard. Built on Telco dataset (7,043 customers). Developed an interactive machine ...