Shape Perception in Human and Computer Vision
https://doi.org/10.1007/978-1-4471-5195-1
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https://doi.org/10.1007/978-1-4471-5195-1
https://doi.org/10.1007/978-1-4471-5283-5
https://doi.org/10.1109/cvpr.2001.990916
10.1109/ICCVW.2017.13
PMC: PMC7619684
With the continues expansion of the application boundary for wireless communications, the application environment of wireless communications is becoming increasingly complex and diverse, which faces negative impacts such as radio frequency ...
Robotic Template Library (RTL) is a set of tools for dealing with geometry and point cloud processing, especially in robotic applications. The software package covers basic objects such as vectors, line segments, quaternions, rigid transfor...
10.5334/jors.353
10.1038/s41746-026-02989-5
PMC: PMC13728136
Reading text and unified text detection and recognition from natural images are the most challenging applications in computer vision and document analysis. Previously proposed end-to-end scene text reading methods do not consider the freque...
10.3390/app10134474
Artificial Intelligence (AI) has promising applications in basketball shooting analysis, as it can help basketball athletes improve their shooting techniques and accuracy, thereby enhancing the effectiveness of both games and training sessi...
10.1109/ACCESS.2023.3304631
https://doi.org/10.1109/cvpr17489.2012
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...
https://doi.org/10.1109/coginf.2010.5599750
Federated Learning (FL) has recently emerged as a novel machine learning paradigm allowing to preserve privacy and to account for the distributed nature of the learning process in many real-world settings. Computer vision tasks deal with hu...
https://doi.org/10.1109/access.2023.3310400
Recent advances in computer vision and deep learning, particularly Convolutional Neural Networks (CNNs), have significantly increased road safety. CNNs were used in this work to automatically detect and categorise traffic signs—a crucial ta...
10.33093/jiwe.2025.4.2.14
Over the last years deep learning methods have been shown to outperform previous state-of-the-art machine learning techniques in several fields, with computer vision being one of the most prominent cases. This review paper provides a brief ...
https://doi.org/10.48175/ijarsct-2898
https://doi.org/10.1016/0031-3203(91)90117-n
With the invention of the low-cost Microsoft Kinect sensor, high-resolution depth and visual (RGB) sensing has become available for widespread use. The complementary nature of the depth and visual information provided by the Kinect sensor o...
https://doi.org/10.1109/tcyb.2013.2265378
With the expeditious advancement in multicarrier automotive in-vehicle monitoring for a bus conforming environment with computer vision, there is an exigency for a setup subsisting on inspection cameras and an onboard embedded computing dev...
10.1109/ACCESS.2025.3637900
Manual medication dispensing in pharmacies remains prone to human errors and is time-intensive, particularly under high patient loads, while existing commercial automation solutions are cost-prohibitive for small to medium-sized pharmacy se...
10.31026/j.eng.2026.08.02
The paper proposes a novel framework for automatically detecting wind turbines in orthophotos, transferring this information to a database, and linking detected turbines to an existing registry to minimize location inaccuracy. This inaccura...
10.5194/isprs-archives-XLVIII-M-7-2025-35-2025
The rapid advancement of Artificial Intelligence (AI), wearable computing, and Internet of Things (IoT) technologies has significantly transformed digital interactions across various sectors. However, the adoption of smart wearable technolo...
10.5281/zenodo.21981139