Abstract: Graph Neural Networks (GNNs) have been gaining more attention due to their excellent performance in modeling various graph-structured data. However, most of the current GNNs only consider ...

A deep learning framework combines convolutional and bidirectional recurrent networks to improve protein function prediction from genomic sequences. By automating feature extraction and capturing long ...

Abstract: A convolutional neural network (CNN)-based architecture for the optimization of demodulation reference signal (DMRS) patterns is proposed for 5G new radio systems. The proposed architecture ...

Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting expertise.From neural networks to N ...

Learn how to build a fully connected, feedforward deep neural network from scratch in Python! This tutorial covers the theory, forward propagation, backpropagation, and coding step by step for a hands ...

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 ...

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 ...

This system uses a neural network to predict NBA game outcomes and total points, with integrated betting strategy tools including Expected Value calculation and Kelly Criterion bet sizing.

Bridging communication gaps between hearing and hearing-impaired individuals is an important challenge in assistive technology and inclusive education. In an attempt to close that gap, I developed a ...