So, while the Nvidia GeForce RTX 5060 has been out for a little over a month, I was finally able to get the Asus Prime model tested this week – and the results have been unsurprising. Just like the ...

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 I vision models have improved dramatically over the past decade. Yet these gains have led to neural networks which, though effective, don’t share many characteristics with human vision. For example, ...

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 ...

Recently, the graph convolutional network (GCN) has drawn increasing attention in the hyperspectral image (HSI) classification. Compared with the convolutional neural network (CNN) with fixed square ...

The main objective of proposed research is to employ DL (Deep Learning) models to predict User-to-Root (U2R) attack using CNN (Convolution Neural Network) Alexnet. In this study, the dataset used was ...

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 ...

Road extraction in remote sensing images has a wide range of applications and is influential in the fields of automatic driving, city planning, navigation, etc. However, there are many shadows, ...

Modeling complex spatiotemporal dependencies in correlated traffic series is essential for traffic prediction. While recent works have shown improved prediction performance by using neural networks to ...

It is becoming important for the client to be able to check whether the AI inference services have been correctly calculated. Since the weight values in a CNN model are assets of service providers, ...