Semantic segmentation is a scene understanding task at the heart of safety-critical applications where robustness to corrupted inputs is essential. Implicit Background Estimation (IBE) has demonstrated to be a promising technique to improve the …
In this paper, we examine the overfitting behavior of image classification models modified with Implicit Background Estimation (SCrIBE), which transforms them into weakly supervised segmentation models that provide spatial domain visualizations …
Semi-supervised learning provides a means to leverage unlabeled data when labels are expensive to obtain. In this work, we propose a constrained framework that better learns from unlabeled data. The proposed algorithm adds an auxiliary task, image …
Scene understanding and semantic segmentation are at the core of many computer vision tasks, many of which, involve interacting with humans in potentially dangerous ways. It is therefore paramount that techniques for principled design of robust …
This paper investigates the application of wavelet analysis to the problem of coherent detection of digital binary frequency shift keying communication signals in additive white Gaussian noise channels. The proposed wavelet-based receiver computes …