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Top Computer Vision Papers of All Time (Updated 2024)

Viso.ai

Today’s boom in computer vision (CV) started at the beginning of the 21 st century with the breakthrough of deep learning models and convolutional neural networks (CNN). In this article, we dive into some of the most significant research papers that triggered the rapid development of computer vision.

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9 Applications of Computer Vision in Law and Legal Systems

Viso.ai

The evolution of computer vision technology has paved the way for innovative artificial intelligence (AI) solutions in the legal industry. Beyond traditional applications like people detection, object tracking, and behavior analysis, computer vision has the potential to offer many more creative and nuanced solutions.

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AlexNet: A Revolutionary Deep Learning Architecture

Viso.ai

AlexNet is an Image Classification model that transformed deep learning. It was introduced by Geoffrey Hinton and his team in 2012, and marked a key event in the history of deep learning, showcasing the strengths of CNN architectures and its vast applications.

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Computer Vision for Cultural Heritage Preservation: Unlocking the Past with Advanced Imaging…

Heartbeat

Computer Vision for Cultural Heritage Preservation: Unlocking the Past with Advanced Imaging Technology Image Source: Technology Innovators Preserving our cultural legacy is critical because it allows us to remain in touch with our past, learn our roots, and appreciate humanity's rich history.

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Classification without Training Data: Zero-shot Learning Approach

Analytics Vidhya

Introduction Computer vision is a field of A.I. Since 2012 after convolutional neural networks(CNN) were introduced, we moved away from handcrafted features to an end-to-end approach using deep neural networks. This article was published as a part of the Data Science Blogathon. These are easy to develop […].

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Understanding the different types and kinds of Artificial Intelligence

IBM Journey to AI blog

However, AI capabilities have been evolving steadily since the breakthrough development of artificial neural networks in 2012, which allow machines to engage in reinforcement learning and simulate how the human brain processes information. Examples include self-driving cars and machines navigating warehouses and other environments.

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Revolutionizing Image Classification: Training Large Convolutional Neural Networks on the ImageNet Dataset

Marktechpost

CNN’s performance improved in the ILSVRC-2012 competition, achieving a top-5 error rate of 15.3%, compared to 26.2% The success of this model reflects a broader shift in computer vision towards machine learning approaches that leverage large datasets and computational power. by the next-best model.