A woodland is a complicated ecosystem consisting in particular of timber that defend the soil and assist limitless varieties of life. It gives many advantages such as regulating the climate, defending ...

Convolutional Neural Networks (CNNs) have been applied effectively to classify high to medium-resolution imageries, especially for local scale land cover mapping, and attained high accuracy by ...

Low-dose computed tomography (LDCT) reduces radiation exposure but suffers from high noise, impacting image quality and diagnostic accuracy. Supervised learning has helped address this challenge but ...

An enhanced 1-D convolutional neural network (1D-CNN)-based fault diagnosis method is proposed. The method begins with the acquisition of fault data, including three-phase voltages on the dc side and ...

Atrial fibrillation (AF) is a prevalent clinical arrhythmia, posing a significant health risk. Efficient diagnosis relies on ECG signals. To enhance timely and accurate AF diagnosis, we propose a ...

Rolling bearing failure will affect the normal operation of the mechanical equipment. Effective early failure diagnosis can avoid unnecessary losses caused by bearing fault. A fault diagnostic method ...

This paper presents a solution addressing the challenges associated with increased screen time during remote work. Leveraging specialized hardware and convolutional neural networks, our real-time ...

A 1D Convolutional Neural Network was developed and validated using experimental data, achieving a classification accuracy of 97% in controlled scenarios. The architecture of the model balances ...

In today’s world AI is becoming more popular, to improve the quality, and result of their product. So, we have also taken some groundbreaking step in the realm of plant disease detection, utilizing ...

To analyse the DeepFakes, which are AI-generated synthetic media that impersonate real people and pose substantial threats to digital content security, privacy, and authenticity. This research ...