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Computer vision for interactive computer graphics

William T. Freeman, David Anderson, Paul A. Beardsley, C.N. Dodge et al. • IEEE Computer Graphics and Applications (1998)

Vision can be a powerful interface device for computers because of its potential for sensing body position, head orientation, direction of gaze, pointing commands, and gestures. Such unencumbered interaction can make computers easier to use...

OPENALEX DOI: https://doi.org/10.1109/38.674971

Structured Learning and Prediction in Computer Vision

Sebastian Nowozin, Christoph H. Lampert • Foundations and Trends® in Computer Graphics and Vision (2011)

Powerful statistical models that can be learned efficiently from large amounts of data are currently revolutionizing computer vision. These models possess a rich internal structure reflecting task-specific relations and constraints. This mo...

OPENALEX DOI: https://doi.org/10.1561/0600000033

Machine Learning in Computer Vision

Asharul Islam Khan, Salim Al-Habsi • Procedia Computer Science (2020)

During last few years the computer applications have gone dramatic transformation from simple data processing to machine learning, thanks to the availability and accessibility of huge volume of data collected through sensors and internet. T...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.procs.2020.03.355

Emerging Trends in Autonomous Vehicle Perception: Multimodal Fusion for 3D Object Detection

Simegnew Yihunie Alaba, Ali C. Gurbuz, John E. Ball • World Electric Vehicle Journal (2024)

The pursuit of autonomous driving relies on developing perception systems capable of making accurate, robust, and rapid decisions to interpret the driving environment effectively. Object detection is crucial for understanding the environmen...

DOAJ Open Access (DOAJ) DOI: 10.3390/wevj15010020

Multi-scale attention and collaborative fusion for enhanced RGB-D salient object detection in weld quality inspection

Zhiwen Xiong, Yuanchun Li • Scientific Reports (2026)

Abstract Salient object detection (SOD) plays a crucial role in computer vision by mimicking human visual attention to identify and segment the most prominent objects in a scene. The advent of depth sensing technologies has propelled RGB-D ...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-026-56237-7

Resource-Aware Scene Text Recognition Using Learned Features, Quantization, and Contour-Based Character Extraction

Olutosin Ajibola Ademola, Eduard Petlenkov, Mairo Leier • IEEE Access (2023)

Scene texts serve as valuable information for humans and autonomous systems to make informed decisions. Processing scene texts poses significant difficulties for computer systems due to several factors, primarily due to variations in image ...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2023.3283931

(Computer) vision without sight

Roberto Manduchi, James M. Coughlan • Communications of the ACM (2011)

Computer vision holds great promise for helping persons with blindness or visual impairments (VI) to interpret and explore the visual world. To this end, it is worthwhile to assess the situation critically by understanding the actual needs ...

OPENALEX Open Access DOI: https://doi.org/10.1145/2063176.2063200 PMC: 3398697

Computer Vision

Xiong Zhihui • InTech eBooks (2008)

This book presents research trends on computer vision, especially on application of robotics, and on advanced approachs for computer vision (such as omnidirectional vision). Among them, research on RFID technology integrating stereo vision ...

OPENALEX Open Access DOI: https://doi.org/10.5772/72

Computer Vision and Image Processing: A Paper Review

Victor Wiley, Thomas Lucas • International Journal of Artificial Intelligence Research (2018)

Computer vision has been studied from many persective. It expands from raw data recording into techniques and ideas combining digital image processing, pattern recognition, machine learning and computer graphics. The wide usage has attracte...

OPENALEX cc-by-sa DOI: https://doi.org/10.29099/ijair.v2i1.42

A computer vision for animal ecology

Ben G. Weinstein • Journal of Animal Ecology (2017)

A central goal of animal ecology is to observe species in the natural world. The cost and challenge of data collection often limit the breadth and scope of ecological study. Ecologists often use image capture to bolster data collection in t...

OPENALEX Open Access DOI: https://doi.org/10.1111/1365-2656.12780

Evaluation of Similarity of Image Explanations Produced by SHAP, LIME and Grad-CAM

Vladyslav Yavtukhovskyi, Violeta Tretynyk • Кібернетика та комп'ютерні технології (2025)

Introduction. Convolutional neural networks (CNNs) are a subtype of neural networks developed specifically to work with images [1]. They have achieved great success both in research and in practical applications in recent years, however, on...

DOAJ Open Access (DOAJ) DOI: 10.34229/2707-451X.25.2.6

Computer vision technology in agricultural automation —A review

Hongkun Tian, Tianhai Wang, Yadong Liu, Xi Qiao et al. • Information Processing in Agriculture (2019)

Computer vision is a field that involves making a machine “see”. This technology uses a camera and computer instead of the human eye to identify, track and measure targets for further image processing. With the development of computer visio...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.inpa.2019.09.006

Computer Vision: Evolution And Promise

Thomas S. Huang • CERN Document Server (European Organization for Nuclear Research) (1996)

In this paper we give a somewhat personal and perhaps biased overview of the field of Computer Vision.First, we define computer vision and give a very brief history of it.Then, we outline some of the reasons why computer vision is a very di...

OPENALEX Open Access DOI: https://doi.org/10.5170/cern-1996-008.21

A review of convolutional neural networks in computer vision

Xia Zhao, Limin Wang, Yufei Zhang, Xuming Han et al. • Artificial Intelligence Review (2024)

Abstract In computer vision, a series of exemplary advances have been made in several areas involving image classification, semantic segmentation, object detection, and image super-resolution reconstruction with the rapid development of dee...

OPENALEX cc-by DOI: https://doi.org/10.1007/s10462-024-10721-6

Computer Vision Metrics

Scott Krig • Apress eBooks (2014)

Computer Vision Metrics provides an extensive survey and analysis of over 100 current and historical feature description and machine vision methods, with a detailed taxonomy for local, regional and global features. This book provides necess...

OPENALEX Open Access DOI: https://doi.org/10.1007/978-1-4302-5930-5