Which Machine Learning Models Are Most Used In Crypto Signal Generation?

Machine learning is transforming how crypto traders create and understand signals. From supervised models such as Random Forests and Gradient Boosting Machines to sophisticated deep learning hybrids ...

Machine learning workflow enables faster, more reliable organic crystal structure prediction

Prediction of crystal structures of organic molecules is a critical task in many industries, especially in pharmaceuticals ...
Frontiers

Brain-Inspired and neurally grounded algorithms in learning and control of advanced robots

In recent years, the field of robotics has undergone significant transformation, driven increasingly by advances in brain-inspired and neurally grounded ...
IEEE

Prediction of Asthma Using Machine Learning Algorithms

Abstract: Asthma, a prevalent chronic respiratory condition, poses significant challenges to public health worldwide. Accurate and early prediction of asthma risk can greatly aid healthcare ...
Devdiscourse

Machine learning to deep learning: The new frontline in global phishing defense

According to the authors, this evolution marks a clear transition from traditional rule-based security toward data-driven, ...
IEEE

Classification of Music Genres based on Machine Learning SVM and CNN

Abstract: This study aims to compare the performance of two classification methods—Support Vector Machine (SVM) and Convolutional Neural Network (CNN)—in identifying music genres based on audio data ...
IEEE

Bi-Level Optimization of Electric Vehicle Charging Scheduling Using Hybrid Genetic Algorithm and Reinforcement Learning

Abstract: The efficient management of electric vehicle (EV) charging infrastructure is critical to meeting the growing demand for sustainable transportation. This study addresses the Electric Vehicle ...

I tried the world’s first ‘AI manicure’ machine. Here’s what happened

That’s the idea behind Umia, billed as the world’s first “ AI manicure machine”. At first glance, it looks more like a ...
IEEE

Decoding Machine Learning Algorithms for DR Detection

Abstract: Diabetic retinopathy is a serious eye disease which can lead to vision defects in diabetic patients. Early detection is important for preventing vision loss. Automating the detection process ...
IEEE

Application of CNN and KNN Algorithms for Casting Defect Classification

The study abstract outlines the utilization of advanced machine learning to identify and categorize casting defects such as Blowholes, Pinholes, and Swell with high precision, recall, and F1-scores.
IEEE

Design and Analysis of an Enhanced Cnn Accelerator for Deep Learning Applications

Abstract: This paper presents an optimized Convolutional Neural Network (CNN) accelerator with a focus on improving power efficiency and computational performance. Traditional CNN accelerators often ...
IEEE

A Hybrid Model using CNN and Genetic Algorithm for Pattern Classification of Interstitial Lung Disease

Abstract: Our objective is to develop an advanced computational approach to classify patterns of Interstitial Lung Disease(ILD) using a Hybrid model of Convolutional Neural Network(CNN) and Genetic ...