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The format can serialize PHP's primitive and compound types, and also properly serializes references. [1] The format was first introduced in PHP 4. [2] In addition to PHP, the format is also used by some third-party applications that are often integrated with PHP applications, for example by Lucene/Solr. [3]
Images, text Object recognition, scene recognition 2014 [15] [16] J. Xiao et al. ImageNet: Labeled object image database, used in the ImageNet Large Scale Visual Recognition Challenge: Labeled objects, bounding boxes, descriptive words, SIFT features 14,197,122 Images, text Object recognition, scene recognition 2009 (2014) [17] [18] [19] J ...
As of 21 January 2025 (two months after PHP 8.4's release), PHP is used as the server-side programming language on 75.0% of websites where the language could be determined; PHP 7 is the most used version of the language with 47.1% of websites using PHP being on that version, while 40.6% use PHP 8, 12.2% use PHP 5 and 0.1% use PHP 4.
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]
A visual hull can be reconstructed from multiple silhouettes of an object. [3] The task of converting multiple 2D images into 3D model consists of a series of processing steps: Camera calibration consists of intrinsic and extrinsic parameters, without which at some level no arrangement of algorithms can work. The dotted line between Calibration ...
To recognize an object in an arbitrary input image, the paper detects features, and then uses RANSAC to find the affine projection matrix which best fits the unified object model to the 2D scene. If this RANSAC approach has sufficiently low error, then on success, the algorithm both recognizes the object and gives the object's pose in terms of ...
Objects detected with OpenCV's Deep Neural Network module (dnn) by using a YOLOv3 model trained on COCO dataset capable to detect objects of 80 common classes. Object detection is a computer technology related to computer vision and image processing that deals with detecting instances of semantic objects of a certain class (such as humans, buildings, or cars) in digital images and videos. [1]
Object recognition – technology in the field of computer vision for finding and identifying objects in an image or video sequence. Humans recognize a multitude of objects in images with little effort, despite the fact that the image of the objects may vary somewhat in different view points, in many different sizes and scales or even when they are translated or rotated.