Edge AI and Vision Alliance’s Post

Convolutional Neural Networks (CNNs) : A Complete Guide

A Gentle Introduction to Graph Neural Networks https://lnkd.in/d9wwyfqi

CNNs are a network with some convolutional and other layers. The convolutional layer has several filters that do a convolutional operation. In other words, CNNs are a class of Neural Networks that have proven very effective in areas of image recognition processing, and classification. Also, convolutional neural networks (CNNs) are a distinct multilayer neural network architecture type. They are designed in such a manner that each filter is convolved with the input volume, resulting in an activation map consisting of neurons. #AILabPage #VinodsBlog https://lnkd.in/dN6V_3j8

Understanding Output Dimensions in Neural Networks for Signal Data Interpretation: A Blog Series https://lnkd.in/dw6ADt_X

Graph Neural Networks (GNNs) represent a paradigm shift in the realm of neural networks, uniquely tailored for graph-structured data. They are pivotal in addressing complex data scenarios where traditional neural networks fall short. This comprehensive article delves into the core functionalities, applications, and future potential of GNNs. #DataAggregation #Deeplearning #EdgelevelPrediction #GNNApplications #GraphConvolutionalNetworks #GraphNeuralNetworks #GraphlevelPrediction #NetworkAnalysis #NodelevelPrediction #NonEuclideanData

Convolutional Neural Networks

A few days back, I published my first Medium article on The History of Convolutional Neural Networks for Image Classification! Here is the link for those interested: https://lnkd.in/e_-a68Jw For visual learners, here's a companion YouTube video link: https://lnkd.in/eFTKBy-A Designing this tour through the major milestones of Computer Vision was a fun and educational exercise. From the early years of CNN (the ‘90s and Le-Net 5), the article goes through the crazy innovations during the 2010s (AlexNet, VGG, Inception, ResNets, etc) to the present era as ConvNets compete with the generalization power of Vision Transformers. #deeplearning #computervision #machinelearning

Comprehensive Analysis of The Performance of Vision State Space Models (VSSMs), Vision Transformers, and Convolutional Neural Networks (CNNs) https://buff.ly/3W71ThN

Useful guide about Neural Networks. https://lnkd.in/dFE97yw2

Convolutional Neural Networks in PyTorch: Image Classification via #TowardsAI → https://bit.ly/3zpQsIQ