The big challenge in deep learning is that you need a lot of data to train the neural network. Fortunately, one of my ...

Edge AI is emerging as a sustainable solution, processing data locally and enhancing security while reducing costs. This ...

One of the most promising aspects of AI in wildfire management is its capacity to detect complex, nonlinear relationships across massive, multidimensional datasets. Traditional fire prediction models ...

posing formidable challenges for conventional data processing/analysis methods. Deep learning (DL) has emerged as a transformative tool to tackle extreme complexity, with a classical model training ...

Neurological disorders, including neurodegenerative diseases, brain tumors, and other conditions like stroke and epilepsy, increasingly burden healthcare ...

swarms for sensor data collection tasks, particularly in uncertain environments. This paper addresses the problem of designing flight strategies for energy-constrained UAV swarms using deep ...

This study introduces advanced predictive frameworks that incorporate enhancements to both deep learning (DL) models and statistical techniques to handle the intricate, nonlinear, and dynamic ...

This dataset is a merged version of three publicly available datasets, refined through preprocessing and augmentation to ensure high-quality and consistent input for deep learning models. Each image ...