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Automatic building detection and land use classification in urban areas using multispectral high-spatial resolution imagery and LiDAR data

Txomin Hermosilla • ELCVIA Electronic Letters on Computer Vision and Image Analysis (2014)

Urban areas areimportant environments, accounting for approximately half the population of theworld. Cities attract residents partly because they offer ample opportunitiesfor development, which often results in urban sprawl and its complex ...

DOAJ Open Access (DOAJ) DOI: 10.5565/rev/elcvia.584

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

Convolutional-de-convolutional neural networks for recognition of surgical workflow

Yu-wen Chen, Ju Zhang, Peng Wang, Zheng-yu Hu et al. • Frontiers in Computational Neuroscience (2022)

Computer-assisted surgery (CAS) has occupied an important position in modern surgery, further stimulating the progress of methodology and technology. In recent years, a large number of computer vision-based methods have been widely used in ...

DOAJ Open Access (DOAJ) DOI: 10.3389/fncom.2022.998096

Sparse Representation for Computer Vision and Pattern Recognition

John N. Wright, Yi Ma, Julien Mairal, Guillermo Sapiro et al. • Proceedings of the IEEE (2010)

Techniques from sparse signal representation are beginning to see significant impact in computer vision, often on nontraditional applications where the goal is not just to obtain a compact high-fidelity representation of the observed signal...

OPENALEX DOI: https://doi.org/10.1109/jproc.2010.2044470

Computer vision: basic principles

Azriel Rosenfeld • Proceedings of the IEEE (1988)

The author provides a general introduction to computer vision. He discusses basic techniques and computer implementations, and also indicates areas in which further research is needed. He focuses on two-dimensional object recognition, i.e. ...

OPENALEX DOI: https://doi.org/10.1109/5.5961

Computer Vision and Pattern Recognition 2020

Zeynep Akata, Andreas Geiger, Torsten Sattler • International Journal of Computer Vision (2021)

This special issue covers a wide range of topics from the area of Computer Vision, Pattern Recognition, and Machine Learning.This breadth of scope is reflected by the papers included in this special issue, which touch topics including geome...

OPENALEX cc-by DOI: https://doi.org/10.1007/s11263-021-01522-3

Deep learning based identification and tracking of railway bogie parts

Muhammad Zakir Shaikh, Zeeshan Ahmed, Enrique Nava Baro, Samreen Hussain et al. • Alexandria Engineering Journal (2024)

The Train Rolling-Stock Examination (TRSE) is a safety examination process that physically examines the bogie parts of a moving train, typically at speeds over 30 km/h. Currently, this inspection process is done manually by railway personne...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.aej.2024.07.064

Computer vision for microscopy diagnosis of malaria

Faik Boray TEK, Andrew Graham Dempster, İzzet Kale • Malaria Journal (2009)

This paper reviews computer vision and image analysis studies aiming at automated diagnosis or screening of malaria infection in microscope images of thin blood film smears. Existing works interpret the diagnosis problem differently or prop...

OPENALEX cc-by DOI: https://doi.org/10.1186/1475-2875-8-153 PMC: 2719653

Rethinking the Inception Architecture for Computer Vision

Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jon Shlens et al. • IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings (2016)

Convolutional networks are at the core of most state of-the-art computer vision solutions for a wide variety of tasks. Since 2014 very deep convolutional networks started to become mainstream, yielding substantial gains in various benchmark...

OPENALEX DOI: https://doi.org/10.1109/cvpr.2016.308

Backhand-Approach-Based American Sign Language Words Recognition Using Spatial-Temporal Body Parts and Hand Relationship Patterns

Ponlawat Chophuk, Kosin Chamnongthai, Krisana Chinnasarn • Sensors (2022)

Most of the existing methods focus mainly on the extraction of shape-based, rotation-based, and motion-based features, usually neglecting the relationship between hands and body parts, which can provide significant information to address th...

DOAJ Open Access (DOAJ) DOI: 10.3390/s22124554