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Comparative Study for Monocular Depth Detection Models on Embedded Systems
Monocular depth detection plays a pivotal role in numerous computer vision applications, particularly on edge devices such as the NVIDIA Jetson Nano, which pose unique constraints in terms of computational resources. This paper presents a t...
A New Approach for Early Detection of Vulnerabilities Across the Automotive Software Development
This paper presents a new approach of evaluating automotive development processes, starting from the early stages of development to the final product. The main objective of this paper is to ensure transparency among stakeholders and provide...
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Multichannel Nonnegative Matrix Factorization With Motor Data-Regularized Activations For Robust Ego-Noise Suppression
The suppression of ego-noise is often addressed using dictionary-based methods where the characteristic spectral structure of ego-noise is approximated by a linear combination of dictionary entries. A blind, entirely audio data-based select...
Estimation Of Fields Using Binary Measurements From A Mobile Agent
In this paper we consider the problem of field estimation using a mobile autonomous agent. The agent is equipped with a sensor which can make noisy binary measurements of the field. We model the field as a sum of radial basis functions, who...
Information-Bottleneck-Based Behavior Representation Learning for Multi-Agent Reinforcement Learning
In multi-agent deep reinforcement learning, extracting sufficient and compact information of other agents is critical to attain efficient convergence and scalability of an algorithm. In canonical frameworks, distilling of such information i...
Toward Semi-Autonomous Stiffness Adaptation of Pneumatic Soft Robots: Modeling and Validation
The constant stiffness of the soft medical robots imposes a cap on their force transmission capacity. To address this limitation, the objective of this study was to investigate the effects of chamber pressure on the stiffness of pneumatic s...