A Convolutional Neural Network (CNN) is a deep learning architecture composed of convolutional layers that automatically extract hierarchical spatial features from input data, such as WiFi CSI amplitude or phase matrices, without requiring manual feature engineering. In WiFi sensing research, CNNs are valuable because they can capture local patterns and structural correlations within CSI signals that are indicative of occupancy levels or human presence, improving counting accuracy over traditional machine learning approaches. A common variant in this domain is the CNN+LSTM hybrid, which combines CNNs for spatial feature extraction with Long Short-Term Memory networks for temporal sequence modeling, enabling the system to exploit both the spatial structure and time-varying dynamics of CSI measurements for more robust people counting.
Source Papers
- A Framework to Estimate Classroom Occupancy using WiFi Channel State Information ↗ — A Framework to Estimate Classroom Occupancy using WiFi Chann
- A Survey on Green Wireless Sensing: Energy-Efficient Sensing via WiFi CSI and Lightweight Learning ↗ — A Survey on Green Wireless Sensing: Energy-Efficient Sensing
- A Survey on Human Behavior Recognition Using Channel State Information ↗ — A Survey on Human Behavior Recognition Using Channel State I
- A Survey on Wireless Device-free Human Sensing: Application Scenarios, Current Solutions, and Open Issues ↗ — A Survey on Wireless Device-free Human Sensing: Application
- A survey of recent advances in CNN-based single image crowd counting and density estimation ↗ — A survey of recent advances in CNN-based single image crowd
- CRPF-QC: An Efficient CSI Recurrence Plot-Based Framework for Queue Counting ↗ — CRPF-QC: An Efficient CSI Recurrence Plot-Based Framework fo
- CSI-Based NTC Using Ambient WiFi: Channel Selection, Topology Control and Traffic Interference ↗ — CSI-Based NTC Using Ambient WiFi: Channel Selection, Topolog
- CSI-Based People Counting in WiFi Networks: Leveraging Occupancy Detection ↗ — CSI-Based People Counting in WiFi Networks: Leveraging Occup
- CSI-Chain: A Complete End-to-End Framework for WiFi CSI Sensing ↗ — CSI-Chain: A Complete End-to-End Framework for WiFi CSI Sens
- Channel State Information (CSI) Amplitude Coloring Scheme for Enhancing Accuracy of an Indoor Occupancy Detection System Using Wi-Fi Sensing ↗ — Channel State Information (CSI) Amplitude Coloring Scheme fo
- Channel State Information from Pure Communication to Sense and Track Human Motion: A Survey ↗ — Channel State Information from Pure Communication to Sense a
- Context-Aware Predictive Coding: A Representation Learning Framework for WiFi Sensing ↗ — Context-Aware Predictive Coding: A Representation Learning F
- Data-driven Crowd Modeling Techniques: A Survey ↗ — Data-driven Crowd Modeling Techniques: A Survey
- Deep Learning-Enhanced Human Sensing with Channel State Information: A Survey ↗ — Deep Learning-Enhanced Human Sensing with Channel State Info
- Device-Free Wireless Sensing for Gesture Recognition Based on Complementary CSI Amplitude and Phase ↗ — Device-Free Wireless Sensing for Gesture Recognition Based o
- Efficient machine learning for Wi-Fi CSI-based human activity recognition using fast Monte Carlo based feature extraction ↗ — Efficient machine learning for Wi-Fi CSI-based human activit
- Exposing the CSI: A Systematic Investigation of CSI-based Wi-Fi Sensing Capabilities and Limitations ↗ — Exposing the CSI: A Systematic Investigation of CSI-based Wi
- MUSE-Fi: Contactless MUti-person SEnsing Exploiting Near-field Wi-Fi Channel Variation ↗ — MUSE-Fi: Contactless MUti-person SEnsing Exploiting Near-fie
- OPERAnet, a multimodal activity recognition dataset acquired from radio frequency and vision-based sensors ↗ — OPERAnet, a multimodal activity recognition dataset acquired
- Occupancy Prediction in IoT-Enabled Smart Buildings: Technologies, Methods, and Future Directions ↗ — Occupancy Prediction in IoT-Enabled Smart Buildings: Technol
- On CSI and Passive Wi-Fi Radar for Opportunistic Physical Activity Recognition ↗ — On CSI and Passive Wi-Fi Radar for Opportunistic Physical Ac
- Passive WiFi Radar for Human Sensing Using a Stand-Alone Access Point ↗ — Passive WiFi Radar for Human Sensing Using a Stand-Alone Acc
- RSSI-Assisted CSI-Based Passenger Counting with Multiple Wi-Fi Receivers ↗ — RSSI-Assisted CSI-Based Passenger Counting with Multiple Wi-
- Recent trends in crowd analysis: A review ↗ — Recent trends in crowd analysis: A review
- SenseFi: A library and benchmark on deep-learning-empowered WiFi human sensing ↗ — SenseFi: A library and benchmark on deep-learning-empowered
- Sensing Technologies for Crowd Management, Adaptation, and Information Dissemination in Public Transportation Systems: A Review ↗ — Sensing Technologies for Crowd Management, Adaptation, and I
- Time matters: Empirical insights into the limits and challenges of temporal generalization in CSI-based Wi-Fi sensing ↗ — Time matters: Empirical insights into the limits and challen
- Towards Environment Independent Device Free Human Activity Recognition ↗ — Towards Environment Independent Device Free Human Activity R
- WiFi Sensing with Channel State Information ↗ — WiFi Sensing with Channel State Information
- WiFi as Infrastructure: Valuation Impact of CSI Sensing on Smart Buildings and REIT Portfolios ↗ — WiFi as Infrastructure: Valuation Impact of CSI Sensing on S
- WiFi-Based Human Sensing With Deep Learning: Recent Advances, Challenges, and Opportunities ↗ — WiFi-Based Human Sensing With Deep Learning: Recent Advances
- WiGNN: WiFi-Based Cross-Domain Gesture Recognition Inspired by Dynamic Topology Structure ↗ — WiGNN: WiFi-Based Cross-Domain Gesture Recognition Inspired
- WiSegRT: Dataset for Site-Specific Indoor Radio Propagation Modeling with 3D Segmentation and Differentiable Ray-Tracing: (Invited Paper) ↗ — WiSegRT: Dataset for Site-Specific Indoor Radio Propagation