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Found 3 papers, 1 papers with code
ARRQP: Anomaly Resilient Real-time QoS Prediction Framework with Graph Convolution
In this paper, we introduce a real-time QoS prediction framework (called ARRQP) with a specific emphasis on improving resilience to anomalies in the data.
TPMCF: Temporal QoS Prediction using Multi-Source Collaborative Features
Even though some recent recurrent neural-network-based architectures can model temporal relationships among QoS data, prediction accuracy degrades due to the absence of other features (e. g., collaborative features) to comprehend the relationship among the user-service interactions.
VStegNET: Video Steganography Networkusing Spatio-Temporal features andMicro-Bottleneck
Traditional image steganography techniques hide the secret image intohigh-frequency regions of the cover images.
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