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🏛️ The Signal Processing Crypt
eess.SP: Where Signal Processing papers rest without their code.
3527
Total Papers
3247
No Code
16
Twilight
264
Has Code
7.5%
Survival Rate
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mm-Pose: Real-Time Human Skeletal Posture Estimation using mmWave Radars and CNNs
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Joint Computation and Communication Design for UAV-Assisted Mobile Edge Computing in IoT
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A joint precoding framework for wideband reconfigurable intelligent surface-aided cell-free network
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A Vision of C-V2X: Technologies, Field Testing and Challenges with Chinese Development
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Towards Massive MIMO 2.0: Understanding spatial correlation, interference suppression, and pilot contamination
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Reconfigurable Intelligent Surface Aided NOMA Networks
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The Road to 6G: Ten Physical Layer Challenges for Communications Engineers
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Convolutional Neural Network Architectures for Signals Supported on Graphs
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ORACLE: Optimized Radio clAssification through Convolutional neuraL nEtworks
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Neural Network Detection of Data Sequences in Communication Systems
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EEG-based Brain-Computer Interfaces (BCIs): A Survey of Recent Studies on Signal Sensing Technologies and Computational Intelligence Approaches and their Applications
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Multibeam for Joint Communication and Sensing Using Steerable Analog Antenna Arrays
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CubeSat Communications: Recent Advances and Future Challenges
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Communication Through a Large Reflecting Surface With Phase Errors
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EEG-TCNet: An Accurate Temporal Convolutional Network for Embedded Motor-Imagery Brain-Machine Interfaces
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Unsupervised and Semi-supervised Anomaly Detection with LSTM Neural Networks
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Intelligent Reflecting Surface Aided Multigroup Multicast MISO Communication Systems
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Transmission Through Large Intelligent Surfaces: A New Frontier in Wireless Communications
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Deep Networks for Direction-of-Arrival Estimation in Low SNR
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Human Activity Recognition using Inertial, Physiological and Environmental Sensors: a Comprehensive Survey
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Convolutional Neural Network based Multiple-Rate Compressive Sensing for Massive MIMO CSI Feedback: Design, Simulation, and Analysis
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M3ER: Multiplicative Multimodal Emotion Recognition Using Facial, Textual, and Speech Cues
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