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AForge.NET is a computer vision and artificial intelligence library originally developed by Andrew Kirillov for the .NET Framework. [2]The source code and binaries of the project are available under the terms of the Lesser GPL and the GPL (GNU General Public License).
This comparison of optical character recognition software includes: OCR engines, that do the actual character identification; Layout analysis software, that divide scanned documents into zones suitable for OCR; Graphical interfaces to one or more OCR engines
Images Railway signal recognition 2023 [67] [68] Philipp Leibner, Fabian Hampel, Christian Schindler Multi-cue pedestrian Multi-cue onboard pedestrian detection dataset is a dataset for detection of pedestrians. The databaset is labeled box-wise. 1092 image pairs with 1776 boxes for pedestrians Images Object recognition and classification 2009 [69]
Tesseract is an optical character recognition engine for various operating systems. [5] It is free software, released under the Apache License. [1] [6] [7] Originally developed by Hewlett-Packard as proprietary software in the 1980s, it was released as open source in 2005 and development was sponsored by Google in 2006.
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]
[9] [10] The last two examples form the subtopic image analysis of pattern recognition that deals with digital images as input to pattern recognition systems. [11] [12] Optical character recognition is an example of the application of a pattern classifier. The method of signing one's name was captured with stylus and overlay starting in 1990.
A convolutional neural network (CNN) is a regularized type of feed-forward neural network that learns features by itself via filter (or kernel) optimization. This type of deep learning network has been applied to process and make predictions from many different types of data including text, images and audio. [1]
OpenALPR is an automatic number-plate recognition library written in C++. [9] The software is distributed in both a commercial cloud based version [1] and open source version. [3] [10] OpenALPR makes use of OpenCV and Tesseract OCR libraries. It could be run as a command-line utility, standalone library, or background process.