Passive sensing via wearable devices and smartphones, combined with machine learning (ML), enables objective, continuous, and noninvasive mental health monitoring. Objective: This study aimed to ...
Businesses with a Mac-first strategy have long enjoyed the perception of inherent security from the Unix-based operating ...
A full-stack web application that uses deep learning to detect and classify plant diseases from leaf images. Built with Next.js, React, TailwindCSS on the frontend and Flask, TensorFlow on the backend ...
Abstract: Federated Learning (FL) has emerged as a promising solution to train IDS models in a distributed manner while preserving data privacy. However, the heterogeneous nature of client data often ...
RNN-DAS is an innovative Deep Learning model based on Recurrent Neural Networks (RNNs) with Long Short-Term Memory (LSTM) cells, developed for real-time Volcano-seismic Signal Recognition (VSR) using ...
Rohith Vegesna is a software engineer specializing in secure, cloud-connected fueling systems, with a strong focus on IoT, real-time monitoring, and cybersecurity.
Intrusion detection systems, long constrained by high false-positive rates and limited adaptability, are being re-engineered ...
Abstract: Nowadays, the IoT (internet of things) botnet has become a huge threat to network security. In response to this threat, we present a cooperative adaptive network intrusion detection system ...
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