Heartbeat

MARCH 1, 2023

Tracking your image classification experiments with Comet ML Photo from nmedia on Shutterstock.com Introduction Image classification is a task that involves training a neural network to recognize and classify items in images. Before being fed into the network, the photos are pre-processed and shrunk to the same size.

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Convolutional Neural Networks Neural Network Auto-classification Categorization 52

Dlabs.ai

JUNE 11, 2019

How to use deep learning (even if you lack the data)? You can create synthetic data that acts just like real data – and so allows you to train a deep learning algorithm to solve your business problem, leaving your sensitive data with its sense of privacy, intact. What is deep learning?

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PyImageSearch

FEBRUARY 6, 2023

Table of Contents Training a Custom Image Classification Network for OAK-D Configuring Your Development Environment Having Problems Configuring Your Development Environment? Furthermore, this tutorial aims to develop an image classification model that can learn to classify one of the 15 vegetables (e.g.,

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Auto-classification Computer Vision Neural Network Deep Learning 144

Unite.AI

AUGUST 29, 2023

Also, in the current scenario, the data generated by different devices is sent to cloud platforms for processing because of the computationally intensive nature of network implementations. To design it, the developers used the gestures data set, and used the data set to train the ProtoNN model with a classification algorithm.

Neural Network 246

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Viso.ai

DECEMBER 22, 2023

Today, the computer vision project has gained enormous momentum in mobile applications, automated image annotation tools , and facial recognition and image classification applications. These deep learning models are central to the advancement of machine learning and AI, particularly in the realm of image processing.

Convolutional Neural Networks 52

Convolutional Neural Networks Computer Vision Neural Network Auto-classification 52

Heartbeat

JUNE 27, 2023

Neural networks leverage the structure and properties of graph and work in a similar fashion. Graph Neural Networks are a class of artificial neural networks that can be represented as graphs. Edge-level tasks , on the other hand, entail edge classification and link prediction.

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Neural Network Convolutional Neural Networks Auto-classification Deep Learning 59

Becoming Human

MARCH 16, 2023

Photo by NASA on Unsplash Hello and welcome to this post, in which I will study a relatively new field in deep learning involving graphs — a very important and widely used data structure. This post includes the fundamentals of graphs, combining graphs and deep learning, and an overview of Graph Neural Networks and their applications.

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