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Geometric modeling and computer vision

Paul J. Besl • Proceedings of the IEEE (1988)

Geometric matching algorithms and geometric representations are examined for point sets, curves, surfaces, volumes, and their space-time trajectories. The author focuses mainly on general-purpose techniques. Geometric matching benefits grea...

OPENALEX DOI: https://doi.org/10.1109/5.5966

Documenting Computer Vision Datasets

Milagros Miceli, Tianling Yang, Laurens Naudts, Martin Schuessler et al. • ACM Conference on Fairness, Accountability, and Transparency (FAccT) (2021)

In industrial computer vision, discretionary decisions surrounding the production of image training data remain widely undocumented. Recent research taking issue with such opacity has proposed standardized processes for dataset documentatio...

OPENALEX cc-by DOI: https://doi.org/10.1145/3442188.3445880

An image based application in Matlab for automated modelling and morphological analysis of insect wings

Shahab Eshghi, Fatemeh Nabati, Shaghayegh Shafaghi, Vahid Nooraeefar et al. • Scientific Reports (2022)

Abstract Despite extensive research on the biomechanics of insect wings over the past years, direct mechanical measurements on sensitive wing specimens remain very challenging. This is especially true for examining delicate museum specimens...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-022-17859-9

Melanoma Lesion Detection and Segmentation Using YOLOv4-DarkNet and Active Contour

Saleh Albahli, Nudrat Nida, Aun Irtaza, Muhammad Haroon Yousaf et al. • IEEE Access (2020)

Melanoma is the skin cancer caused by the ultraviolet radiation from the Sun and has only 15-20% of survival rate. Late diagnosis of melanoma leads to the severe malignancy of disease, and metastasis expands to the other body organs i.e. li...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2020.3035345

Computer vision vs. human vision

Bo Zhang • IEEE International Conference on Cognitive Informatics (2010)

In object recognition (classification), it was known that the human brain processes visual information in semantic space mainly, that is, extracting the semantically meaningful features such as line-segments, boundaries, shape and so on. Bu...

OPENALEX DOI: https://doi.org/10.1109/coginf.2010.5599750

TransCat: a hybrid CNN-transformer network with KAN for medical image segmentation

Jin Wang, Zhenghua Yang, Dongming Zhou, Dongming Zhou et al. • Frontiers in Bioinformatics (2026)

Medical image segmentation is a fundamental task in computer vision and plays an important role in clinical diagnosis and treatment planning. Existing methods are mainly built on either convolutional neural networks (CNNs) or Transformer-ba...

DOAJ Open Access (DOAJ) DOI: 10.3389/fbinf.2026.1849059

Reliable Parkinson’s Disease Detection by Analyzing Handwritten Drawings: Construction of an Unbiased Cascaded Learning System Based on Feature Selection and Adaptive Boosting Model

Liaqat Ali, Ce Zhu, Noorbakhsh Amiri Golilarz, Ashir Javeed et al. • IEEE Access (2019)

Parkinson's disease (PD) is the second most common neurodegenerative disease of central nervous system (CNS). Till now, there is no definitive clinical examination that can diagnose a PD patient. However, it has been reported that PD patien...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2019.2932037

Mapping the Unknown: Using Incomplete Evidence to Craft Digital Three-Dimensional Models of St Stephen’s

Anthony Masinton, James Jago • British Art Studies (2020)

Crafting a digital reconstruction of a lost space is a process of rediscovery and exploration. The nature of the evidence determines the form of the reconstruction, providing a sketch of what is known about the space. The process of reconst...

DOAJ Open Access (DOAJ) DOI: 10.17658/issn.2058-5462/issue-16/amasinton

PAMPAS: real-valued graphical models for computer vision

Michael Isard • IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings (2003)

Probabilistic models have been adopted for many computer vision applications, however inference in high-dimensional spaces remains problematic. As the state-space of a model grows, the dependencies between the dimensions lead to an exponent...

OPENALEX DOI: https://doi.org/10.1109/cvpr.2003.1211410

Assessing Wireless Sensing Potential With Large Intelligent Surfaces

Cristian J. Vaca-Rubio, Pablo Ramirez-Espinosa, Kimmo Kansanen, Zheng-Hua Tan et al. • IEEE Open Journal of the Communications Society (2021)

Sensing capability is one of the most highlighted new feature of future 6G wireless networks. This paper addresses the sensing potential of Large Intelligent Surfaces (LIS) in an exemplary Industry 4.0 scenario. Besides the attention receiv...

DOAJ Open Access (DOAJ) DOI: 10.1109/OJCOMS.2021.3073467

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