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Showing 20 of 227 academic articles

Computer vision for computer games

William T. Freeman, Kazuhiro Tanaka, Jun Ohta, Kazuo Kyuma • International Conference on Automatic Face and Gesture Recognition (2002)

The appeal of computer games may be enhanced by vision-based user inputs. The high speed and low cost requirements for near-term, mass-market game applications make system design challenging. The response time of the vision interface should...

OPENALEX DOI: https://doi.org/10.1109/afgr.1996.557250

A Deep Learning-Driven Computer Vision and Web-Based Monitoring System for Automated Nutrient Management in Soilless Agriculture

Eda Nur Urtekin, Emre Dandıl • Journal of Agricultural Sciences (2026)

Sustainable food production increasingly relies on intelligent automation technologies that optimize resource usage while maintaining crop health. This study presents a deep learning-driven computer vision and web based monitoring system de...

DOAJ Open Access (DOAJ) DOI: 10.15832/ankutbd.1817471

Computer Vision for Human-Machine Interaction

• Cambridge University Press eBooks (1998)

Advances in the field of computer vision are leading to radical changes in the way we interact with computers. At the time of this book's publication in 1998, it would soon be possible to enable a computer linked to a video camera to detect...

OPENALEX DOI: https://doi.org/10.1017/cbo9780511569937

HawkEye: AI-Driven Software for Objective Analysis and Characterization of Nodular Cast Iron Microstructures

Javier Nieves, Antonio Serena-Barriuso, Guillermo Elejoste-Rementeria • Applied Sciences (2025)

Metallographic evaluation of nodular cast iron is crucial for quality control in the foundry industry. Traditionally, this process relies on experts who visually interpret microscopic images. This study introduces HawkEye, a comprehensive s...

DOAJ Open Access (DOAJ) DOI: 10.3390/app15136991

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

Computer vision in the interface

Matthew Turk • Communications of the ACM (2004)

There are still obstacles to achieving general, robust, high-performance computer vision systems. The last decade, however, has seen significant progress in vision technologies for human-computer interaction....

OPENALEX DOI: https://doi.org/10.1145/962081.962107

Efficient One-Dimensional Network Design Method for Underwater Acoustic Target Recognition

Qing Huang, Xiaoyan Zhang, Anqi Jin, Menghui Lei et al. • Journal of Marine Science and Engineering (2025)

Many studies have used various time-frequency feature extraction methods to convert ship-radiated noise into three-dimensional (3D) data suitable for computer vision (CV) models, which have shown good results in public datasets. However, tr...

DOAJ Open Access (DOAJ) DOI: 10.3390/jmse13030599

(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

Crowdsourcing in Computer Vision

Adriana Kovashka, Olga Russakovsky, Li Fei-Fei, Kristen Lorraine Grauman • now publishers, Inc. eBooks (2016)

Computer vision systems require large amounts of manually annotated data to properly learn challenging visual concepts. Crowdsourcing platforms offer an inexpensive method to capture human knowledge and understanding, for a vast number of v...

OPENALEX Open Access DOI: https://doi.org/10.1561/9781680832136

Distribution of Marbling Throughout the M. Longissimus Thoracis et Lumborum of Beef Carcasses Using an Instrument-Grading System

Clinton E. Walenciak, Dale R Woerner, Michael J. Colle, Phillip D. Bass et al. • Meat and Muscle Biology (2018)

Beef Loin, Strip Loins (IMPS #180; n = 20) with marbling scores between Modest00 and Modest30 at the 12th and 13th rib interface of the M. longissimus thoracis et lumborum (LL) were collected. Each strip loin was fabricated into 6 samples t...

DOAJ Open Access (DOAJ) DOI: 10.22175/mmb2018.04.0005

Deep learning in electron microscopy

Jeffrey M. Ede • Machine Learning Science and Technology (2020)

Abstract Deep learning is transforming most areas of science and technology, including electron microscopy. This review paper offers a practical perspective aimed at developers with limited familiarity. For context, we review popular applic...

OPENALEX cc-by DOI: https://doi.org/10.1088/2632-2153/abd614

Deep Learning with R

François Chollet, JJ Allaire (2018)

Introduces deep learning systems using the powerful Keras library and its R language interface. The book builds your understanding of deep learning through intuitive explanations and practical examples...

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