Scientific Research Publishing

A Combination Method of Stacked Convolutional Auto-Encoder and Selective Kernel Attention Mechanism for Image Classification

With the basic structure and parameters of the model remaining unchanged, this section analyzes and compares two types of network structures with input image sizes of 128 × 128 and 256 × 256. The ...
Visual Studio Magazine

Convolutional Neural Networks for MNIST Data Using PyTorch

Dr. James McCaffrey of Microsoft Research details the "Hello World" of image classification: a convolutional neural network (CNN) applied to the MNIST digits dataset. The "Hello World" of image ...
IEEE

Supervised Convolutional Encoder-Decoder With Gated Linear Units for Detecting Fetal R-Peaks

Abstract: Noninvasive fetal electrocardiography (ECG) is prevalently used for monitoring fetal heartbeats during pregnancy due to its affordability, ease of use, and constant monitoring capability. A ...
PNAS

Convolutional neural networks outperform other presence-only species distribution modeling algorithms

Species distribution models (SDMs) often overlook critical spatial heterogeneity and multiscale environmental patterns, which limit their predictive accuracy for species occurrences. We demonstrate ...
IEEE

Implementation of Convolutional encoder and Viterbi decoder using Verilog HDL

Abstract: A Viterbi decoder uses the Viterbi algorithm for decoding a bit stream that has been encoded using Forward error correction based on a Convolutional code ...
GitHub

IEEE-802.16e Convolutional Turbo Code

The Convolutional Turbo Code hardware implementation meets the Wireless MAN OFDMA PHY CTC encoder specification of the IEEE 802.16e standard.
GitHub

davidecoccoluto/lte_4g_coders_vhdl

This repository contains synthesizable VHDL implementations of Turbo and Convolutional Encoders and Decoders used in 4G LTE systems. It aims to provide a free, open-source, and high-performance ...