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Thermal cameras have become portable enough to integrate into wearables, such as glasses, and can be used maliciously to infer passwords observing heat traces left on keyboards, keypads and screens. While prior work showed how AI-driven approaches can ...
In this demo, we present RTAT, a real-time arm tracking system that tracks both orientation and location of a smartwatch simultaneously by a multitask learning neural network. We incorporate an attention layer and design a dedicated loss for the ...
Obtaining fine-grained structural information about building through ubiquitous sensors is crucial for assessing their aging and damage. However, due to the energy requirements, traditional sensors deployed in the building structure need frequent ...
Continuous monitoring of cardiac health through single-lead wearable Electrocardiogram (ECG), is important for paroxysmal Atrial Fibrillation (AF) detection. Wearable ECG straps, watches, and implantable loop recorders (ILR) are based on this paradigm. ...
In this demonstration, we present a wearable haptic system to realize the perceptual illusion in a virtual environment. We collect the pressure data from sensors attached with the fingertip, and after passing through a classifier, we render the ...
Fine-grained air pollution data is essential for smart living and efficient city management. However, it is arduous to obtain accurate air pollution data with high spatial and temporal resolutions via mobile crowdsensing (MCS) under limited budgets. ...
Current autonomous checkout is often enable by the use of multiple overhead cameras and/or load sensors on shelf, which is limited by the occlusion and dense deployment. We present MOOCA, an origami-inspired low-cost configurable surface structure as ...
In this work, we demonstrate a radically novel approach towards inertial-only tracking of wrist in real-time on a smartwatch for air-writing tasks. Deriving motion trajectories from commercial-grade Inertial Measurement Units (IMU) has always been a ...
Deep learning (DL) has been used for wireless signal analysis in many applications, e.g., indoor localization. By collecting measurement data of wireless signals from the environment, DL models can be trained to accurately predict the change of signal ...
We present a demonstration of our English–to–Indian languages (Hindi, Bengali, Gujarati, Marathi, Punjabi) product review translation system, ReviewMT1. The system is based on the neural machine translation (NMT) model which is used to translate the ...
“Fake News” and Misinformation can have far-reaching negative social impacts. Scalable fake news classification techniques for resource-poor languages such as Hindi are in their infancy due to the lack of data sets and lack of robust NLP libraries in ...
Machine Learning (ML) is more than just training models, the whole life-cycle must be considered. Once deployed, a ML model needs to be constantly managed, supervised and debugged to guarantee its availability, validity and robustness in dynamic ...
Conversational agents have been widely adopted in dialogue systems for various business purposes. Many existing conversational agents are rule-based and require significant human intervention to adapt the knowledge and conversational flow. In this paper,...
Artificial intelligence (AI) planning models play an important role in decision support systems for disaster management e.g. typhoon contingency plan development. However, constructing an AI planning model always requires significant amount of manual ...
Agents can individually devise plans and coordinate to achieve common goals. Methods exist to factor planning problems into separate tasks and distribute the plan synthesis process, while reducing the overall planning complexity. Merging distributedly ...
Value alignment is a crucial aspect of ethical multiagent systems. An important step toward value alignment is identifying values specific to an application context. However, identifying context-specific values is complex and cognitively demanding. To ...
This paper describes a demonstration setup that integrates cognitive agents with the latest W3C standardization efforts for the Web of Things (WoT). The conceptual foundations of the implemented system are the integration of cognitive agent abstractions ...
In recent years, machine learning (ML) models have been successfully applied in a variety of real-world applications. However, they are often complex and incomprehensible to human users. This can decrease trust in their outputs and render their usage in ...
Modeling vessel movement in a maritime environment is an extremely challenging task given the complex nature of vessel behavior. Several existing multiagent maritime decision making frameworks require access to an accurate traffic simulator. We develop ...
We present an extension of the organizational model and infrastructure adopted in JaCaMo, that explicitly encompasses the notion of exception. We propose an exception handling mechanism for organization management in multi-agent systems. This mechanism ...