Facial expressions are at the heart of everyday social interaction and communication. Their absence, such as in Virtual Reality settings, or due to conditions like Parkinson’s disease, can significantly impact commun...
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Task decomposition is a fundamental mechanism in program synthesis, enabling complex problems to be broken down into manageable subtasks. ExeDec, a state-of-the-art program synthesis framework, employs this approach b...
How do we switch between playing along and treating robots as technical agents? We propose interaction breakdowns to help solve this social artifact puzzle: Breaks cause changes from fluid interaction to explicit reas...
As machine learning (ML) models for image perception continue to advance, ensuring their robustness and reliability under various real-world scenarios remains a significant challenge. Image quality factors, such as bl...
As machine learning (ML) models for image perception continue to advance, ensuring their robustness and reliability under various real-world scenarios remains a significant challenge. Image quality factors, such as blur, brightness, and other environmental conditions, can significantly affect the performance of these algorithms, leading to inaccurate detection and potential failures in critical applications. In this paper, we propose a comprehensive diagnosis framework that leverages image quality metrics to assess and enhance the performance of these algorithms. To accomplish this goal, we deliberately introduce disturbances in parameters such as brightness, saturation, and other relevant factors. Subsequently, we compute a set of full-reference image quality metrics to evaluate the image quality after the perturbations. Once we have obtained the metrics, we apply a nonlinear transformation to these values. Based on the transformed metrics, we create a regression model that predicts the detection Intersection over Union (IOU). To validate our framework, we conducted experiments using three state-of-the-art machine learning models for object detection and instance segmentation. The models were subjected to various scenarios with different levels of image quality perturbations. Our experimental results clearly demonstrate the possibility of establishing a strong correlation between image quality metrics and the performance of the algorithms.
Cyber-physical production systems are composed of a multitude of subsystems from diverse vendors and integrators, connected in a distributed fashion. An undesirable phenomenon in one system might cause a misbehavior i...
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In this paper, we consider the problem where a drone has to collect semantic information to classify multiple moving targets. In particular, we address the challenge of computing control inputs that move the drone to ...
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EEG, Electroencephalography, is the acquisition and decoding of electric brain signals. The data acquired from EEG scans can be put to use in many fields, including seizure prediction, treatment of mental illness, bra...
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Cyber physical production systems (CPPS) focus on increasing the flexibility and adaptability of industrial production systems, systems that comprise hardware such as sensors and actuators in machines as well as softw...
ISBN:
(数字)9781728189567
ISBN:
(纸本)9781728189574
Cyber physical production systems (CPPS) focus on increasing the flexibility and adaptability of industrial production systems, systems that comprise hardware such as sensors and actuators in machines as well as software controlling and integrating these machines. The requirements of customised mass production imply that control and integration software needs to be adaptable after deployment in a shop floor (factory), possibly even without interrupting production. Today, software frameworks provide support to model and execute manufacturing processes. They, however, provide little support for reuse. In this paper, we present a framework based on capabilities, which supports manufacturing process templates. These templates are bound/allocated to a specific shopfloor setup, a specific set of machines, and executed using a distributed set of process engines. This enables the reuse of manufacturing processes, as well as transmitting and executing changed processes. The framework is implemented using the Eclipse Milo implementation of OPC UA in Java. It is used to control a lab-scale modular shopfloor programmed in IEC61499 and Java.
Consciousness has been historically a heavily debated topic in engineering, science, and philosophy. On the contrary, awareness had less success in raising the interest of scholars in the past. However, things are cha...
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Robust point cloud registration in real-time is an important prerequisite for many mapping and localization algorithms. Traditional methods like ICP tend to fail without good initialization, insufficient overlap or in...
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