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Found 7 papers, 0 papers with code
Automatic Measures for Evaluating Generative Design Methods for Architects
Of interest for architects is to use these methods to generate design proposals from conceptual sketches, usually hand-drawn sketches that are quickly developed and can embody a design intent.
Sensor Control for Information Gain in Dynamic, Sparse and Partially Observed Environments
We present an approach for autonomous sensor control for information gathering under partially observable, dynamic and sparsely sampled environments that maximizes information about entities present in that space.
On-board Deep-learning-based Unmanned Aerial Vehicle Fault Cause Detection and Identification
With the increase in use of Unmanned Aerial Vehicles (UAVs)/drones, it is important to detect and identify causes of failure in real time for proper recovery from a potential crash-like scenario or post incident forensics analysis.
Deep Multi-Task Learning for Anomalous Driving Detection Using CAN Bus Scalar Sensor Data
In this paper, we present a novel multi-task learning based approach that leverages domain-knowledge (maneuver labels) for anomaly detection in driving data.
Argus: Smartphone-enabled Human Cooperation via Multi-Agent Reinforcement Learning for Disaster Situational Awareness
The agents are involved in capturing the images of the scene using their smartphones (or on-board cameras in case of drones) as directed by the MARL algorithm.
Multi-agent Reinforcement Learning
reinforcement-learning
+1
HCFContext: Smartphone Context Inference via Sequential History-based Collaborative Filtering
Furthermore, since privacy is a concern in collaborative filtering, a privacy-preserving method is proposed to derive HCFContext model parameters based on the concepts of homomorphic encryption.
CollabLoc: Privacy-Preserving Multi-Modal Localization via Collaborative Information Fusion
Mobile phones provide an excellent opportunity for building context-aware applications.
