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Computer Vision Techniques in Manufacturing

Longfei Zhou, Zhang Li, Nicholas Konz • IEEE Transactions on Systems Man and Cybernetics Systems (2022)

Computer vision techniques have played an important role in promoting the informatization, digitization and intelligence of industrial manufacturing systems. Considering the rapid development of computer vision techniques, we present a comp...

OPENALEX Open Access DOI: https://doi.org/10.1109/tsmc.2022.3166397

Robust Techniques for Computer Vision

Peter Meer, B. Tordoff, P. H. S. Torr, C. Davidson et al. (2004)

ysis 1995, pages 191--208. AddisonWesley Longman, 1996. [116] R. H. Zamar. Robust estimation in the errors-in-variables model. Biometrika, 76:149-- 160, 1989. [117] Z. Zhang. Determining the epipolar geometry and its uncertainty: A review. ...

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A Fully Unsupervised Deep Learning Framework for Non-Rigid Fundus Image Registration

Giovana A. Benvenuto, Marilaine Colnago, Maurício A. Dias, Rogério G. Negri et al. • Bioengineering (2022)

In ophthalmology, the registration problem consists of finding a geometric transformation that aligns a pair of images, supporting eye-care specialists who need to record and compare images of the same patient. Considering the registration ...

DOAJ Open Access (DOAJ) DOI: 10.3390/bioengineering9080369

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

Spatially Aware Fusion in 3D Convolutional Autoencoders for Video Anomaly Detection

Asim Niaz, Sareer Ul Amin, Shafiullah Soomro, Hamza Zia et al. • IEEE Access (2024)

Surveillance videos are crucial for crime prevention and public safety, yet the challenge of defining abnormal events hinders their effectiveness, limiting the applicability of supervised methods. This paper introduces an unsupervised end-t...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2024.3435144

Strawberry plant wetness detection using computer vision and deep learning

Arth Patel, Won Suk Lee, Natalia A. Peres, Clyde W. Fraisse • Smart Agricultural Technology (2021)

Botrytis fruit rot and anthracnose are fungal diseases of strawberry. These diseases are a significant contributor to yield losses, requiring farmers to use fungicides frequently to prevent them. The proliferation of botrytis and anthracnos...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.atech.2021.100013

Generalized Vision-Based Detection, Identification and Pose Estimation of Lamps for BIM Integration

Francisco Troncoso-Pastoriza, Javier López-Gómez, Lara Febrero-Garrido • Sensors (2018)

This paper introduces a comprehensive approach based on computer vision for the automatic detection, identification and pose estimation of lamps in a building using the image and location data from low-cost sensors, allowing the incorporati...

DOAJ Open Access (DOAJ) DOI: 10.3390/s18072364

Florence: A New Foundation Model for Computer Vision

Lu Yuan, Dongdong Chen, Yi‐Ling Chen, Noel Codella et al. • arXiv (Cornell University) (2021)

Automated visual understanding of our diverse and open world demands computer vision models to generalize well with minimal customization for specific tasks, similar to human vision. Computer vision foundation models, which are trained on d...

OPENALEX Open Access DOI: https://doi.org/10.48550/arxiv.2111.11432

Ear biometrics in computer vision

Mark J. Burge, Wilhelm Burger • Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition (2002)

A class of biometrics based upon ear features is introduced for use in the development of passive identification systems. The viability of the proposed biometric is shown both theoretically in terms of the uniqueness and measurability over ...

OPENALEX DOI: https://doi.org/10.1109/icpr.2000.906202