AI sheds light on hard-to-study ocean currents

The Indonesian Throughflow carries both warm water and fresh water from the Pacific into the Indian Ocean. As the only ...
IEEE

An Ensemble Deep Learning Model Using CNN, LSTM and Autoencoder for EEG-Based Parkinson’s Disease Classification

Abstract: Parkinson's disease is a neurological disorder hat effects the movements including shaking, stiffness, difficulty while walking and speaking. This condition will occur when the nerve cells ...
IEEE

A CNN and Deep Learning-based Smart Satellite Surveillance System for Wildfire Detection and Wildlife Damage Assessment

Abstract: Wildfires are a growing concern due to their catastrophic impacts on the environment, ecosystem services, biodiversity, and human settlements. Different fire detection systems face ...
IEEE

Faster R-CNN vs SSD: A Deep Learning Approach for Nodule Detection in Lung Cancer Diagnosis

Abstract: Deep learning-based object identification technology has numerous uses, including facial recognition, commercial analytics, and medical imaging analysis. An object detector has a backbone ...
IEEE

Hybrid CNN-LSTM Model for Accurate Time Series Forecasting: A Deep Learning Approach

Abstract: Time series data analysis is essential in a variety of fields, such as finance, meteorology, and healthcare. Traditional methods often struggle to capture the complex temporal correlations ...
IEEE

Deep Learning Models for Precision Agriculture: Evaluating CNN Architectures for Accurate Plant Disease Detection

Abstract: Early and precise detection of plant diseases is crucial for enhancing crop yield and minimizing agricultural losses. This paper evaluates the performance of deep learning-based ...
GitHub

Metis: AI-Powered Security Code Review

Metis is an open-source, AI-driven tool for deep security code review, created by Arm's Product Security Team. It helps engineers detect subtle vulnerabilities, improve secure coding practices, and ...
IEEE

State-of-the-Art Review of Deep Learning-based Computer Vision Waste Detection: R-CNN, YOLO, Transformers, and Hybrid Models

Abstract: Effective waste detection remains a pressing challenge due to the variability, clutter, and inconsistent visual characteristics of waste environments. This state-of-the-art review rigorously ...
IEEE

Deep Learning-Based Malaria Detection: A Robust CNN Framework for Accurate and Automated Diagnosis

Abstract: This research suggests a strong framework for automated malaria detection using a Convolutional Neural Network (CNN) model. The dataset, sourced from Kaggle, consists of 27,558 ...