The automation of daily tasks via the Internet of Things (IoT) has drastically changed people’s lives in the last few years. By connecting different physical devices with various functionalities, this ...

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 ...

The drug discovery process is well known to be lengthy and costly, making it imperative that new approaches are explored to increase the efficiency with which novel therapeutic candidates can be ...

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 ...

In recent years, neural network-based methods have shown promising results in hyperspectral image (HSI) denoising areas. Real HSIs exhibit the substantial variations in noise distribution due to ...

This paper presents a novel methodology for predicting network traffic in complex and dynamic environments. In order to tackle the difficulties associated with precise forecasting of network traffic ...

Multiple object tracking is a critical task in autonomous driving. Existing works primarily focus on the heuristic design of neural networks to obtain high accuracy. As tracking accuracy improves, ...

Impact of Colour Image and Skeleton Plotting on Sign Language Recognition Using Convolutional Neural Networks (CNN) Published in: 2024 14th International Conference on Cloud Computing, Data Science & ...

In this study, we propose a novel structure of hierarchical neural networks (HNN) realized by long short-term memory (LSTM), two classes of self-organizing dynamical fuzzy neural network architectures ...

Model interpretability is a requirement in many applications in which crucial decisions are made by users relying on a model's outputs. The recent movement for “algorithmic fairness” also stipulates ...

It enables the generation of MSD as the first output digit and usage in consecutive computations in digit serial manner leading to different benefits like low latency, high throughput, variable ...