Remove Categorization Remove Computer Vision Remove Deep Learning
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Role of Fully Convolutional Networks in Semantic Segmentation

Analytics Vidhya

Introduction Semantic segmentation, categorizing images pixel-by-pixel into specified groups, is a crucial problem in computer vision. Fully Convolutional Networks (FCNs) were first introduced in a seminal publication by Trevor Darrell, Evan Shelhamer, and Jonathan Long in 2015.

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Your Guide to Object Detection with Detectron2 in PyTorch

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Object detection is one of the popular applications of deep learning. Most of you would have used Google Photos in your phone, which automatically categorizes your photos into groups based on the objects present in them under […].

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Computer vision gives global manufacturer another set of eyes

SAS Software

Computer vision is a field of artificial intelligence that teaches computers to understand visuals. Using digital images from cameras and videos and deep learning models, machines can learn to recognize and categorize objects and respond to their surroundings based on what they “see.”

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Top Computer Vision Tools/Platforms in 2023

Marktechpost

Computer vision enables computers and systems to extract useful information from digital photos, videos, and other visual inputs and to conduct actions or offer recommendations in response to that information. Human vision has an advantage over computer vision because it has been around longer.

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A Decade of Transformation: How Deep Learning Redefined Stereo Matching in the Twenties

Marktechpost

A fundamental topic in computer vision for nearly half a century, stereo matching involves calculating dense disparity maps from two corrected pictures. According to their cost-volume computation and optimization methodologies, existing surveys categorize end-to-end architectures into 2D and 3D classes.

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This Paper Explores the Application of Deep Learning in Blind Motion Deblurring: A Comprehensive Review and Future Prospects

Marktechpost

Computer vision tasks like autonomous driving, object segmentation, and scene analysis can negatively impact this effect, which blurs or stretches the image’s object contours, diminishing their clarity and detail. There has been a meteoric rise in the use of deep learning in image processing in the past several years.

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Image Classification Model trained using Google Colab

Analytics Vidhya

Two popular types of categorization techniques are […]. Introduction Image classification is the process of classifying and recognizing groups of pixels inside an image in line with pre-established principles. Using one or more spectral or text qualities is feasible while creating the classification regulations.