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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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Computer Vision Tasks (Comprehensive 2024 Guide)

Viso.ai

Computer vision (CV) is a rapidly evolving area in artificial intelligence (AI), allowing machines to process complex real-world visual data in different domains like healthcare, transportation, agriculture, and manufacturing. Future trends and challenges Viso Suite is an end-to-end computer vision platform.

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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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AI Emotion Recognition and Sentiment Analysis (2025)

Viso.ai

AI emotion recognition is a very active current field of computer vision research that involves facial emotion detection and the automatic assessment of sentiment from visual data and text analysis. provides the end-to-end computer vision platform Viso Suite. About us: Viso.ai

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Introduction of Neural Style Transfer – A Pioneer in Generative AI

Towards AI

In computer vision, there is an area called domain adaptation or style transfer which generates a new image by mixing up specific attributes from different images. However, generative models is not a new term and it has come a long way since Generative Adversarial Network (GAN) was published in 2014 [1].

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Allen Institute for Artificial Intelligence (AI2) Announces New CEO

Allen AI

Founded in 2014, AI2 is the research institute created by the late philanthropist Paul G. Allen School of Computer Science & Engineering at University of Washington, Farhadi’s research impact has been globally recognized with several best paper awards at CVPR, NeruIPS, AAAI, NSF Career Award, and the Sloan Fellowship.

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Crack Detection in Concrete

Towards AI

Photo by Maud CORREA on Unsplash Computer Vision Using Computer Vision Introduction Crack detection is crucial in monitoring the health of infrastructural buildings. Therefore, Now we conquer this problem of detecting the cracks using image processing methods, deep learning algorithms, and Computer Vision.