Fuzz-IEEE

Abstract: Deep learning (DL) is producing state-of-the-art results in a number of unmanned aerial vehicle (UAV) tasks from low level signal processing to object detection, 3D mapping, tracking, fusion, autonomy, control, and beyond. However, barriers exist. For example, most DL algorithms require big data, but supervised ground truth is a bottlenec... k, fueling topics like self-supervised learning. While it is well-known that hardware and data augmentation plays a significant role in performance, it is not well understood which data augmentations or what real data need be collected. Furthermore, existing datasets do not have sufficient ground truth nor variety to support adequate controlled experimental research into understanding and mitigating limitations in DL algorithms, models, data, and biases. In this article, we address the combination of photorealistic simulation, open source libraries, and high quality content (models, materials, and environments) to develop workflows to mitigate the above challenges and accelerate DL-enabled computer vision research. Herein, examples are provided relative to data collection, detection, passive ranging, and human-robot teaming. Online video tutorials are also provided at URL . Abstract: Zadehs extension principle (ZEP) is a fundamental concept in fuzzy set (FS) theory that enables crisp mathematical operation on FSs. A well-known shortcoming of ZEP is that the height of the output FS is determined by the lowest height of the input FSs. In this article, we introduce a generalized extension principle (GEP) that eliminates this weakness and provides flexibility and control over how membership values are mapped from input to output. Furthermore, we provide a computationally efficient point-based FS representation. In light of our new definition, we discuss two approaches to perform aggregation of FSs using the Choquet integral. The resultant integrals generalize prior work and lay a foundation for future extensions. Last, we demonstrate the extended integrals via a ...Read More