Abstract: Learned image compression has attracted considerable interests in recent years. An analysis transform and a synthesis transform, which can be regarded as coupled transforms, are used to ...

Overview: Seven carefully selected OpenCV books guide beginners from basics to advanced concepts, combining theory, coding ...

This project implements a Spiking Neural Network (SNN) using the Brian2 neuromorphic simulator, featuring biologically-inspired Spike-Timing-Dependent Plasticity (STDP) learning. The network is ...

Eric Gutiérrez, 6th February 2026. A Python implementation of a 1-hidden layer neural network built entirely from first principles. This project avoids deep learning libraries (like TensorFlow or ...

Abstract: This paper introduces a control framework that leverages Lagrangian neural networks (LNNs) for computed torque control (CTC) of robotic systems with unknown dynamics. Unlike prior LNN-based ...

The Heisenberg uncertainty principle puts a limit on how precisely we can measure certain properties of quantum objects. But researchers may have found a way to bypass this limitation using a quantum ...

Experts believe the snakes may be dispersing from the Everglades as their population grows, using connected waterways as highways. While not considered an overwhelming threat to humans, pythons can ...

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 ...

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...

3D rendering—the process of converting three-dimensional models into two-dimensional images—is a foundational technology in computer graphics, widely used across gaming, film, virtual reality, and ...