Computer Vision Research Discipline
A Computer Vision Research Discipline is a computing research discipline that studies automated vision and automated vision algorithms (to develop automated vision systems).
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- See: Object Detection Task, Object Recognition Task, Computer Vision Discipline, Mobile Robot, Machine Vision, Automated Species Identification, Industrial Robots, Activity Recognition, Artificial Intelligence for Video Surveillance, People Counter, Presto (Restaurant Technology), Computer-Human Interaction, Autonomous Vehicle, Computer-Assisted Diagnosis, Image Restoration, Image Sensor, Image Processing, Image Analysis, High-Dimensional, Scientific Discipline.
References
2020
- (Wikipedia, 2020) ⇒ https://en.wikipedia.org/wiki/Computer_vision Retrieved:2020-8-13.
- Computer vision is an interdisciplinary scientific field that deals with how computers can gain high-level understanding from digital images or videos. From the perspective of engineering, it seeks to understand and automate tasks that the human visual system can do.
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 forms of decisions. Understanding in this context means the transformation of visual images (the input of the retina) into descriptions of the world that make sense to thought processes and can elicit appropriate action. This image understanding can be seen as the disentangling of symbolic information from image data using models constructed with the aid of geometry, physics, statistics, and learning theory.
The scientific discipline of computer vision is concerned with the theory behind artificial systems that extract information from images. The image data can take many forms, such as video sequences, views from multiple cameras, multi-dimensional data from a 3D scanner or medical scanning device. The technological discipline of computer vision seeks to apply its theories and models to the construction of computer vision systems.
Sub-domains of computer vision include scene reconstruction, event detection, video tracking, object recognition, 3D pose estimation, learning, indexing, motion estimation, visual servoing, 3D scene modeling, and image restoration.
- Computer vision is an interdisciplinary scientific field that deals with how computers can gain high-level understanding from digital images or videos. From the perspective of engineering, it seeks to understand and automate tasks that the human visual system can do.
2020
- http://cvpr2020.thecvf.com/submission/main-conference/author-guidelines#call-for-papers
- QUOTE: opics of interest include all aspects of computer vision and pattern recognition including, but not limited to
3D computer vision Action and behavior recognition Adversarial learning, adversarial attack and defense methods Biometrics, face, gesture, body pose Computational photography, image and video synthesis Datasets and evaluation Efficient training and inference methods for networks Explainable AI, fairness, accountability, privacy, transparency and ethics in vision Image retrieval Low-level and physics-based vision Machine learning architectures and formulations Medical, biological and cell microscopy Motion and tracking Neural generative models, auto encoders, GANs Optimization and learning methods Recognition (object detection, categorization) Representation learning, deep learning Scene analysis and understanding Segmentation, grouping and shape Transfer, low-shot, semi- and un- supervised learning Video analysis and understanding Vision + language, vision + other modalities Vision applications and systems, vision for robotics and autonomous vehicles Visual reasoning and logical representation
2009
- Master's Degree in Statistics at the University of Chicago. http://www.stat.uchicago.edu/admissions/ms-degree.html
- Computer Vision: Object recognition and detection, in medical imaging, regular photos, digitized documents and a variety of other sources - is a recurrent and critical issue in science, industry and modern communications. The faculty includes specialists in the analysis of visual signals.