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Computer vision tasks include methods for acquiring, processing, analyzing, and understanding digital images, and extraction of high-dimensional data from the real world in order to produce numerical or symbolic information, e.g. in the form of decisions. [1][2][3][4] "Understanding" in this context signifies the transformation of visual images ...
Digital image processing is the use of a digital computer to process digital images through an algorithm. [1][2] As a subcategory or field of digital signal processing, digital image processing has many advantages over analog image processing. It allows a much wider range of algorithms to be applied to the input data and can avoid problems such ...
The ImageNet project is a large visual database designed for use in visual object recognition software research. More than 14 million [1][2] images have been hand-annotated by the project to indicate what objects are pictured and in at least one million of the images, bounding boxes are also provided. [3] ImageNet contains more than 20,000 ...
Deep learning is a subset of machine learning that focuses on utilizing neural networks to perform tasks such as classification, regression, and representation learning. The field takes inspiration from biological neuroscience and is centered around stacking artificial neurons into layers and "training" them to process data.
Machine vision is the technology and methods used to provide imaging -based automatic inspection and analysis for such applications as automatic inspection, process control, and robot guidance, usually in industry. Machine vision refers to many technologies, software and hardware products, integrated systems, actions, methods and expertise.
It shows the outer surface (red), the surface between compact bone and spongy bone (green) and the surface of the bone marrow (blue). In digital image processing and computer vision, image segmentation is the process of partitioning a digital image into multiple image segments, also known as image regions or image objects (sets of pixels).
v. t. e. Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions. [1]
A widely cited paper nicknamed word2vec revolutionizes the processing of text in machine learnings. It shows how each word can be converted into a sequence of numbers (word embeddings), the use of these vectors revolutionized text processing in machine learning. 2014: Achievement: Leap in Face Recognition