In this paper we propose a methodology for robust 3D object recognition using uncertain image data. In particular, we present a method capable of achieving ...
In this paper we propose a methodology for robust 3D object recognition using uncertain image data. In particular, we present a method capable of achieving ...
Camps: Towards a Robust Physics-Based Object Recognition System. Object Representation in Computer Vision 1994: 297-311(PDF, BibTex). 1993. Mario Sznaier ...
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The tool performs physics simulation to place objects at realistic configurations and renders images of scenes to generate a synthetic dataset to train an ...
We present a robust object detection method to detect generic objects with incompact, complex and changeable shapes without training.
Jul 1, 2024 · Abstract. Deep learning-based lane detection (LD) plays a critical role in autonomous driving systems, such as adap- tive cruise control.
Missing: Physics- | Show results with:Physics-
At the same time, physics- based approaches lack realism in noise patterns but main- tain image integrity. The third option is to do denoising and then detect ...
Our approach automatically identifies corner cases where CNNs fail and improves their robustness by automated augmentation of the training data with synthetic.
Missing: Physics- | Show results with:Physics-
To that end, this paper presents techniques to realize robust and edge-based deep learning computer vision applications thereby providing a level of assured ...
Mar 1, 2024 · In this paper, we present a modular approach for reconstructing lensless measurements. It consists of three components: a newly-proposed pre-processor, a ...