Input quality aware convolutional LSTM networks for virtual marine sensors
Sign Up to like & getrecommendations! Published in 2018 at "Neurocomputing"
DOI: 10.1016/j.neucom.2017.11.027
Abstract: The harsh environmental conditions in a marine area make continuous observations of it challenging. To temporally or permanently replace faulty hardware sensors, reliable virtual sensors are getting more and more important. This paper introduces a… read more here.
Keywords: quality; quality aware; aware convolutional; input quality ... See more keywords
Beyond the Shortest Route: A Survey on Quality-Aware Route Navigation for Pedestrians
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DOI: 10.1109/access.2020.3011924
Abstract: Navigation systems often aid users when traveling in unfamiliar locations. Current navigation systems tend to focus on identifying the shortest or fastest routes between two points. However, path cost expressed in terms of length and… read more here.
Keywords: route navigation; quality aware; route; navigation systems ... See more keywords
Rethinking Deep CNN Training: A Novel Approach for Quality-Aware Dataset Optimization
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Access"
DOI: 10.1109/access.2024.3414651
Abstract: The informativeness of data has always been of great interest within the machine learning community. Nowadays, with the skyrocketing advancement of artificial intelligence and massive volumes of noisy data, it becomes even more essential to… read more here.
Keywords: novel approach; approach quality; aware dataset; quality aware ... See more keywords
Link-Quality Aware Path Selection in the Presence of Proactive Jamming in Fallible Wireless Sensor Networks
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Transactions on Communications"
DOI: 10.1109/tcomm.2017.2736550
Abstract: In this paper, we propose a mechanism to ensure the proper functioning of a wireless sensor network (WSN) in the presence of static and proactive jammer within the network. Existing research works have primarily focused… read more here.
Keywords: quality; link quality; network; quality aware ... See more keywords
Quality-Aware Spatio-Temporal Transformer Network for RGBT Tracking
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Transactions on Image Processing"
DOI: 10.1109/tip.2025.3635483
Abstract: Transformer-based RGBT tracking has attracted much attention due to the strong modeling capacity of self attention and cross attention mechanisms. These attention mechanisms utilize the correlations among tokens to construct powerful feature representations, but are… read more here.
Keywords: quality; search; template tokens; spatio temporal ... See more keywords
Quality-Aware Incentive Mechanisms Under Social Influences in Data Crowdsourcing
Sign Up to like & getrecommendations! Published in 2022 at "IEEE/ACM Transactions on Networking"
DOI: 10.1109/tnet.2021.3105427
Abstract: Incentive mechanism design and quality control are two key challenges in data crowdsourcing, because of the need for recruitment of crowd users and their limited capabilities. Without considering users’ social influences, existing mechanisms often result… read more here.
Keywords: quality; quality aware; incentive mechanisms; data crowdsourcing ... See more keywords
Quality-Aware Resource Model Discovery
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DOI: 10.3390/app11125730
Abstract: Context-aware process mining aims at extending a contemporary approach with process contexts for realistic process modeling. Regarding this discipline, there have been several attempts to combine process discovery and predictive process modeling and context information,… read more here.
Keywords: process; resource; quality aware; resource model ... See more keywords
Data Quality-Aware Client Selection in Heterogeneous Federated Learning
Sign Up to like & getrecommendations! Published in 2024 at "Mathematics"
DOI: 10.3390/math12203229
Abstract: Federated Learning (FL) enables decentralized data utilization while maintaining edge user privacy, but it faces challenges due to statistical heterogeneity. Existing approaches address client drift and data heterogeneity issues. However, real-world settings often involve low-quality… read more here.
Keywords: quality; client selection; data quality; federated learning ... See more keywords