Image processing and computer vision on mobile devices have a wide range of applications such as digital image enhancement and augmented reality. While ima
the Kitti vision benchmark suite. In: 2012 IEEE Conference on computer vision and pattern recognition, pp 3354–3361.https://doi.org/10.1109/CVPR.2012.6248074 Ghafoorian M, Nugteren C, Baka N, Booij O, Hofmann M (2018) El-gan: embedding loss driven generative adversarial networks for lane ...
The STL models could be used for computer vision applications such as instrument detection, segmentation, or tracking, as well as in medical mixed-reality simulation scenarios. To this end, the models can be integrated with game engines, such as Unity3D or Unreal Engine, to create mixed-...
Semantic segmentation is an extensively studied task in computer vision, with numerous methods proposed every year. Thanks to the advent of deep learning i
Semantic scene completion (SSC) aims to jointly estimate the complete geometry and semantics of a scene, assuming partial sparse input. In the last years f
(Maddern et al.2017; Sattler et al.2018), depicting the city of Oxford, UK under various seasonal conditions, and the University of Michigan North Campus Long-Term Vision and LIDAR (Carlevaris-Bianco et al.2016) datasets use Lidar data to obtain reference poses. However, human intervention ...
Kim, Y.; Kang, B.-N.; Kim, D. San: Learning Relationship between Convolutional Features for Multi-Scale Object Detection. In Proceedings of the European Conference on Computer Vision (ECCV), Munich, Germany, 8–14 September 2018; pp. 316–331. [Google Scholar] Real, E.; Aggarwal, A....
pothole detection; computer vision; image processing; machine learning; deep learning; target detection; convolutional neural networks 1. Introduction In the current world, the quality of road infrastructure plays a crucial role in facilitating economic activities, social interaction, and public safety [...
2024. "A Real-Time Automated Defect Detection System for Ceramic Pieces Manufacturing Process Based on Computer Vision with Deep Learning" Sensors 24, no. 1: 232. https://doi.org/10.3390/s24010232 APA Style Cumbajin, E., Rodrigues, N., Costa, P., Miragaia, R., Frazão, L., ...
The crux of label-efficient semantic segmentation is to produce high-quality pseudo-labels to leverage a large amount of unlabeled or weakly labeled data.