Analytics Insight

Best Neural Networks Courses in 2026 for AI and Deep Learning

Overview Neural networks courses in 2026 focus heavily on practical deep learning frameworks such as TensorFlow, PyTorch, and ...
Scientific Research Publishing

Cybersecurity and Forensic Audio Analysis: Deepfake Detection Based on Mfcc, Audio-Text Disconsistency, and Prosodic Features ()

1 Department of Computer and Instructional Technologies Education, Gazi Faculty of Education, Gazi University, Ankara, Türkiye. 2 Department of Forensic Informatics, Institute of Informatics, Gazi ...
IEEE

Hybrid Quantum Convolutional Neural Network-Aided Pilot Assignment in Cell-Free Massive MIMO Systems

Abstract: A sophisticated hybrid quantum convolutional neural network (HQCNN) is conceived for handling the pilot assignment task in cell-free massive MIMO systems, while maximizing the total ergodic ...
Hosted on MSN

Neural network Python from scratch with softmax

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 ...
TMCnet

Bridging Silence: A Real-Time Sign Language to English Text Translation System Using Python, OpenCV, and Convolutional Neural Networks

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 ...
Hosted on MSN

Build a deep neural network from scratch in Python

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 ...
Beebom

What is CNN in Deep Learning? The AI Behind Computer Vision

CNN in deep learning is a special type of neural network that can understand images and visual information. It works just like human vision: first it detects edges, lines and then recognizes faces and ...
IEEE

A Convolutional Neural Network to Spiking Neural Network Conversion Framework for Seismic Denoising

Abstract: This study investigates the application of Spiking Neural Network (SNN) in seismic signal denoising by developing a Convolutional Neural Network (CNN) to SNN conversion framework. We focus ...
Electronic Design

A Neural-Network-Based Approach to Smarter DPD Engines

An AI-driven digital-predistortion (DPD) framework can help overcome the challenges of signal distortion and energy inefficiency in power amplifiers for next-generation wireless communication.