Image analysisImage analysis or imagery analysis is the extraction of meaningful information from s; mainly from s by means of techniques. Image analysis tasks can be as simple as reading bar coded tags or as sophisticated as identifying a person from their face. Computers are indispensable for the analysis of large amounts of data, for tasks that require complex computation, or for the extraction of quantitative information.
Deep learningDeep learning is part of a broader family of machine learning methods, which is based on artificial neural networks with representation learning. The adjective "deep" in deep learning refers to the use of multiple layers in the network. Methods used can be either supervised, semi-supervised or unsupervised.
Oldest dated rocksThe oldest dated rocks formed on Earth, as an aggregate of minerals that have not been subsequently broken down by erosion or melted, are more than 4 billion years old, formed during the Hadean Eon of Earth's geological history. Meteorites that were formed in other planetary systems can pre-date Earth. Particles from the Murchison meteorite were dated in January 2020 to be 7 billion years old. Hadean rocks are exposed on Earth's surface in very few places, such as in the geologic shields of Canada, Australia, and Africa.
Transient lunar phenomenonA transient lunar phenomenon (TLP) or lunar transient phenomenon (LTP) is a short-lived light, color or change in appearance on the surface of the Moon. The term was created by Patrick Moore in his co-authorship of NASA Technical Report R-277 Chronological Catalog of Reported Lunar Events, published in 1968. Claims of short-lived lunar phenomena go back at least 1,000 years, with some having been observed independently by multiple witnesses or reputable scientists.
Edge detectionEdge detection includes a variety of mathematical methods that aim at identifying edges, curves in a at which the image brightness changes sharply or, more formally, has discontinuities. The same problem of finding discontinuities in one-dimensional signals is known as step detection and the problem of finding signal discontinuities over time is known as change detection. Edge detection is a fundamental tool in , machine vision and computer vision, particularly in the areas of feature detection and feature extraction.
Corner detectionCorner detection is an approach used within computer vision systems to extract certain kinds of features and infer the contents of an image. Corner detection is frequently used in motion detection, , video tracking, image mosaicing, panorama stitching, 3D reconstruction and object recognition. Corner detection overlaps with the topic of interest point detection. A corner can be defined as the intersection of two edges. A corner can also be defined as a point for which there are two dominant and different edge directions in a local neighbourhood of the point.
Pupillary distancePupillary distance (PD), more correctly known as interpupillary distance (IPD) is the distance in millimeters between the centers of each pupil. Distance PD is the separation between the visual axes of the eyes in their primary position, as the subject fixates on an infinitely distant object. Near PD is the separation between the visual axes of the eyes, at the plane of the spectacle lenses, as the subject fixates on a near object at the intended working distance. Intermediate PD is at a specified plane in between distance and near.
Training, validation, and test data setsIn machine learning, a common task is the study and construction of algorithms that can learn from and make predictions on data. Such algorithms function by making data-driven predictions or decisions, through building a mathematical model from input data. These input data used to build the model are usually divided into multiple data sets. In particular, three data sets are commonly used in different stages of the creation of the model: training, validation, and test sets.
Attention (machine learning)Machine learning-based attention is a mechanism mimicking cognitive attention. It calculates "soft" weights for each word, more precisely for its embedding, in the context window. It can do it either in parallel (such as in transformers) or sequentially (such as recursive neural networks). "Soft" weights can change during each runtime, in contrast to "hard" weights, which are (pre-)trained and fine-tuned and remain frozen afterwards. Multiple attention heads are used in transformer-based large language models.
Pedestrian detectionPedestrian detection is an essential and significant task in any intelligent video surveillance system, as it provides the fundamental information for semantic understanding of the video footages. It has an obvious extension to automotive applications due to the potential for improving safety systems. Many car manufacturers (e.g. Volvo, Ford, GM, Nissan) offer this as an ADAS option in 2017.
