Abstract: Deep Learning(DL) has emerged as a significant area of research across various fields, particularly in healthcare. The identification of irregularities in Electrocardiogram (ECG) readings is ...

Classic fault detection and classification has some classic problems. It’s reactive, time-consuming to set up, and any product change involves significant man-hours. Even then, it still misses a lot ...

Explore the first part of our series on sleep stage classification using Python, EEG data, and powerful libraries like Sklearn and MNE. Perfect for data scientists and neuroscience enthusiasts!

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...

In an era of rapidly growing multimedia data, the need for robust and efficient classification systems has become critical, specifically the identification of class names and poses or styles. This ...

1 Center for Cyberspace Studies, Nasarawa State University, Keffi, Nigeria. 2 Department of Computer Engineering, Nile University of Nigeria, Abuja, Nigeria. 3 Department of Public and International ...

Introduction: Integrating immune repertoire sequencing data with single cell sequencing data offers profound insights into the diversity of immune cells and their dynamic changes across various ...

In this tutorial, we demonstrate how to efficiently fine-tune the Llama-2 7B Chat model for Python code generation using advanced techniques such as QLoRA, gradient checkpointing, and supervised ...

Abstract: Industrial and agricultural use requires fruit colour, size, shape, and texture classification. Classification enhances sorting, grading, quality control, and customer satisfaction.

The code is partially associated with the following papers: Spatial Prior Fuzziness Pool-Based Interactive Classification of Hyperspectral Images and Multiclass Non-Randomized Spectral–Spatial Active ...