Computer vision applications in intelligent transportation systems (ITS) and autonomous driving (AD) have gravitated towards deep neural network architectures in recent years. While performance seems to be improving on benchmark datasets, many real-world challenges are yet to be adequately considered in ...
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
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....
Xu et al., (2023) proposed a Vision-IMU-based detection and ranging (VIDAR)-based approach for pothole detection, combining vision and IMU sensors. Their method focused on filtering, marking, and framing potholes on flat pavements using MSER for dimension estimation [4]. By comparing their ...
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.
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., ...