IEEE

Bone Fracture Classification Using Deep Learning Models with Transfer Learning

Abstract: Bone fracture can be defined as the complete or partial disruption of the integrity of bone tissue. Early and accurate diagnosis of fractures plays a decisive role in the effectiveness of ...
IEEE

Remote Sensing Scene Image Classification with Swin Transformer-Based Transfer Learning

Abstract: In remote sensing classification problems, high visual similarity between scenes reduces the classification performance of traditional methods. Therefore, advanced deep neural network models ...
IEEE

Probabilistic Forecasting for Battery Health Estimation Using CNN-LSTM on Augmented Multi-Operation Data

Abstract: Ensuring the safety and reliability of electric vehicles and energy storage systems requires an effective evaluation of lithium-ion battery State of Health (SOH). Most current methods are ...
IEEE

Early Detection of Paddy Disease and Severity Based Classification Using Variants of CNN - A Step Towards Smart Agriculture

Abstract: Agriculture is the backbone of India, and in the southern region, paddy is the main crop, grown twice a year. Over the years, paddy fields have been affected by different diseases, out of ...
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

Memristor based Crossbar Array using CNN for Image Processing Applications

Abstract: Image processing has become one of the popular neuromorphic computing applications in recent years. Most of the application areas require an efficient and real time image processing system.
IEEE

Helmet Detection in Two Wheeler Using Image Processing

Abstract: Road safety is a significant concern worldwide, with a high number of fatalities occurring due to the negligence of helmet usage by two-wheeler riders. According to statistics, thousands of ...
IEEE

Secure Spread Spectrum Image Steganography Using a CNN-Based Learned Detector

Abstract: Spread Spectrum Image Steganography (SSIS) represents a promising approach for embedding secret data into a cover image. In conventional methods, a pseudo-noise (PN) sequence functions as a ...
TMCnet

Bridging Silence: A Real-Time Sign Language to English Text Translation System Using Python, OpenCV, and Convolutional Neural Networks

Bridging communication gaps between hearing and hearing-impaired individuals is an important challenge in assistive technology and inclusive education. In an attempt to close that gap, I developed a ...
CNN

How to avoid getting into trouble when using AI at work

Love it or hate it, AI is increasingly becoming integral to the way we work. So, like a lot of employees, you’ve started using it for your assignments. That’s great – unless you’re not clear on what ...
IEEE

Automated Sleep Stage Classification Using Multi-Channel EEG Time-Frequency Features and CNN-BiLSTM Hybrid Networks

Abstract: This research presents a high-accuracy deep learning framework for automated sleep stage classification, leveraging a hybrid CNN-BiLSTM architecture combined with multi-channel EEG ...