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Human Pose Estimation with Deep Learning – Ultimate Overview in 2024

Viso.ai

This article will explore the latest advances in pose analytics algorithms and AI vision techniques, their applications and use cases, and their limitations. Today, the most powerful image processing models are based on convolutional neural networks (CNNs). Definition: What is pose estimation?

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How to Create Synthetic Data to Train Deep Learning Algorithms?

Dlabs.ai

How to use deep learning (even if you lack the data)? To train a computer algorithm when you don’t have any data. Read on to learn how to use deep learning in the absence of real data. What is deep learning? First, let’s (briefly) tackle an important question: What is deep learning?

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Understanding Graph Neural Network with hands-on example| Part-1

Becoming Human

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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TinyML: Applications, Limitations, and It’s Use in IoT & Edge Devices

Unite.AI

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. However, the implementation did not generalize effectively to images within new use cases as well as backgrounds with noise.

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Train and host a computer vision model for tampering detection on Amazon SageMaker: Part 2

AWS Machine Learning Blog

In the first part of this three-part series, we presented a solution that demonstrates how you can automate detecting document tampering and fraud at scale using AWS AI and machine learning (ML) services for a mortgage underwriting use case. We provide guidance on building, training, and deploying deep learning networks on Amazon SageMaker.