Bridging communication gaps between hearing and hearing-impaired individuals is an important challenge in assistive ...

While some AI courses focus purely on concepts, many beginner programs will touch on programming. Python is the go-to language for AI because it’s relatively easy to learn and has a massive library of ...

🎮 Train a Deep Q-Learning agent using TensorFlow to master Atari Breakout with efficient experience replay and modular architecture for easy customization.

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write the code, but it's entirely from scratch in python. We will code Deep Neural ...

Quantum convolutional neural networks (QCNNs) represent a promising approach in quantum machine learning, paving new directions for both quantum and classical data analysis. This approach is ...

Abstract: Recently, deep learning has transformed machine learning by significantly enhancing its artificial intelligence as Artificial Neural Networks (ANN) have become increasingly prevalent. Due of ...

Code for paper “FusionGCN: Multi-focus image fusion using superpixel features generation GCN and pixel-level feature reconstruction CNN”（ESWA, 2025） ...

Forecasting groundwater changes is a crucial step towards effective water resource planning and sustainable management. Conventional models still demonstrated insufficient performance when aquifers ...

Abstract: This study introduces a novel strategy for waste segregation employing Convolutional Neural Networks (CNNs) and Python programming. By harnessing CNNs’ image feature extraction capabilities, ...