{"total":80,"rows":[{"id":"2310.10196","title":"Large Models for Time Series and Spatio-Temporal Data: A Survey and Outlook","created":"2023-10-16","cited_by_count":110,"area":null},{"id":"2111.00418","title":"Deep Learning in Human Activity Recognition with Wearable Sensors: A Review on Advances","created":"2021-10-31","cited_by_count":54,"area":null},{"id":"2108.08910","title":"Achieving on-Mobile Real-Time Super-Resolution with Neural Architecture and Pruning Search","created":"2021-08-18","cited_by_count":34,"area":null},{"id":"2310.20071","title":"FOCAL: Contrastive Learning for Multimodal Time-Series Sensing Signals in Factorized Orthogonal Latent Space","created":"2023-10-30","cited_by_count":33,"area":null},{"id":"2108.00702","title":"Improving Deep Learning for HAR with shallow LSTMs","created":"2021-08-02","cited_by_count":30,"area":null},{"id":"2202.00758","title":"ColloSSL: Collaborative Self-Supervised Learning for Human Activity Recognition","created":"2022-02-01","cited_by_count":22,"area":null},{"id":"2106.00615","title":"Meta-HAR: Federated Representation Learning for Human Activity Recognition","created":"2021-05-31","cited_by_count":21,"area":null},{"id":"2207.12577","title":"Compiler-Aware Neural Architecture Search for On-Mobile Real-time Super-Resolution","created":"2022-07-25","cited_by_count":20,"area":null},{"id":"2410.02592","title":"IC3M: In-Car Multimodal Multi-object Monitoring for Abnormal Status of Both Driver and Passengers","created":"2024-10-03","cited_by_count":20,"area":null},{"id":"2104.09949","title":"DynO: Dynamic Onloading of Deep Neural Networks from Cloud to Device","created":"2021-04-20","cited_by_count":18,"area":null},{"id":"2407.06628","title":"Masked Video and Body-worn IMU Autoencoder for Egocentric Action Recognition","created":"2024-07-09","cited_by_count":18,"area":null},{"id":"2110.13290","title":"Exploring System Performance of Continual Learning for Mobile and Embedded Sensing Applications","created":"2021-10-25","cited_by_count":17,"area":null},{"id":"2309.07438","title":"Towards Artificial General Intelligence (AGI) in the Internet of Things (IoT): Opportunities and Challenges","created":"2023-09-14","cited_by_count":14,"area":null},{"id":"2404.13528","title":"SmartMem: Layout Transformation Elimination and Adaptation for Efficient DNN Execution on Mobile","created":"2024-04-21","cited_by_count":12,"area":null},{"id":"2404.01958","title":"MESEN: Exploit Multimodal Data to Design Unimodal Human Activity Recognition with Few Labels","created":"2024-04-02","cited_by_count":11,"area":null},{"id":"2310.09114","title":"Timestamp-supervised Wearable-based Activity Segmentation and Recognition with Contrastive Learning and Order-Preserving Optimal Transport","created":"2023-10-13","cited_by_count":10,"area":null},{"id":"2404.15349","title":"A Survey on Multimodal Wearable Sensor-based Human Action Recognition","created":"2024-04-14","cited_by_count":10,"area":null},{"id":"2508.09085","title":"Dynamic Uncertainty-aware Multimodal Fusion for Outdoor Health Monitoring","created":"2025-08-12","cited_by_count":10,"area":null},{"id":"2410.07230","title":"RFBoost: Understanding and Boosting Deep WiFi Sensing via Physical Data Augmentation","created":"2024-10-04","cited_by_count":9,"area":null},{"id":"2202.08922","title":"FLAME: Federated Learning Across Multi-device Environments","created":"2022-02-17","cited_by_count":8,"area":null},{"id":"2501.13066","title":"SMART-Vision: Survey of Modern Action Recognition Techniques in Vision","created":"2025-01-22","cited_by_count":8,"area":null},{"id":"2111.11581","title":"Automatic Mapping of the Best-Suited DNN Pruning Schemes for Real-Time Mobile Acceleration","created":"2021-11-22","cited_by_count":7,"area":null},{"id":"2205.13607","title":"Self-supervised Pretraining and Transfer Learning Enable Flu and COVID-19 Predictions in Small Mobile Sensing Datasets","created":"2022-05-26","cited_by_count":7,"area":null},{"id":"2208.07929","title":"ViT-ReT: Vision and Recurrent Transformer Neural Networks for Human Activity Recognition in Videos","created":"2022-08-16","cited_by_count":7,"area":null},{"id":"2301.03462","title":"Unleashing the Power of Shared Label Structures for Human Activity Recognition","created":"2023-01-01","cited_by_count":7,"area":null},{"id":"2303.03789","title":"Fast and Multi-aspect Mining of Complex Time-stamped Event Streams","created":"2023-03-07","cited_by_count":7,"area":null},{"id":"2410.00003","title":"Large Language Model-Guided Semantic Alignment for Human Activity Recognition","created":"2024-09-12","cited_by_count":6,"area":null},{"id":"2508.12213","title":"Towards Generalizable Human Activity Recognition: A Survey","created":"2025-08-17","cited_by_count":6,"area":null},{"id":"2312.05790","title":"SimPSI: A Simple Strategy to Preserve Spectral Information in Time Series Data Augmentation","created":"2023-12-10","cited_by_count":5,"area":null},{"id":"2501.15070","title":"Unifying Prediction and Explanation in Time-Series Transformers via Shapley-based Pretraining","created":"2025-01-25","cited_by_count":5,"area":null},{"id":"2102.05956","title":"The Benefit of the Doubt: Uncertainty Aware Sensing for Edge Computing Platforms","created":"2021-02-11","cited_by_count":4,"area":null},{"id":"2403.00176","title":"SoD$^2$: Statically Optimizing Dynamic Deep Neural Network","created":"2024-02-29","cited_by_count":4,"area":null},{"id":"2404.02461","title":"On the Efficiency and Robustness of Vibration-based Foundation Models for IoT Sensing: A Case Study","created":"2024-04-03","cited_by_count":4,"area":null},{"id":"2402.03714","title":"Advancing Location-Invariant and Device-Agnostic Motion Activity Recognition on Wearable Devices","created":"2024-02-06","cited_by_count":3,"area":null},{"id":"2404.15351","title":"Integrating Physiological Data with Large Language Models for Empathic Human-AI Interaction","created":"2024-04-14","cited_by_count":3,"area":null},{"id":"2105.08643","title":"ASM2TV: An Adaptive Semi-Supervised Multi-Task Multi-View Learning Framework for Human Activity Recognition","created":"2021-05-18","cited_by_count":2,"area":null},{"id":"2107.06097","title":"Transformer-Based Behavioral Representation Learning Enables Transfer Learning for Mobile Sensing in Small Datasets","created":"2021-07-09","cited_by_count":2,"area":null},{"id":"2110.00244","title":"Lightweight Transformer in Federated Setting for Human Activity Recognition","created":"2021-10-01","cited_by_count":2,"area":null},{"id":"2203.04153","title":"Easy Ensemble: Simple Deep Ensemble Learning for Sensor-Based Human Activity Recognition","created":"2022-03-08","cited_by_count":2,"area":null},{"id":"2402.02275","title":"SudokuSens: Enhancing Deep Learning Robustness for IoT Sensing Applications using a Generative Approach","created":"2024-02-03","cited_by_count":2,"area":null},{"id":"2407.19414","title":"Appformer: A Novel Framework for Mobile App Usage Prediction Leveraging Progressive Multi-Modal Data Fusion and Feature Extraction","created":"2024-07-28","cited_by_count":2,"area":null},{"id":"2409.15973","title":"Edge-device Collaborative Computing for Multi-view Classification","created":"2024-09-24","cited_by_count":2,"area":null},{"id":"2503.13542","title":"HAR-DoReMi: Optimizing Data Mixture for Self-Supervised Human Activity Recognition Across Heterogeneous IMU Datasets","created":"2025-03-16","cited_by_count":2,"area":null},{"id":"2607.18361","title":"Physical Self-Supervised Learning: IMU Sensing without Manual Labels","created":"2026-07-20","cited_by_count":2,"area":null},{"id":"2105.13533","title":"Inertial Sensor Data To Image Encoding For Human Action Recognition","created":"2021-05-28","cited_by_count":1,"area":null},{"id":"2106.15283","title":"Similarity Embedding Networks for Robust Human Activity Recognition","created":"2021-05-31","cited_by_count":1,"area":null},{"id":"2108.10213","title":"SALIENCE: An Unsupervised User Adaptation Model for Multiple Wearable Sensors Based Human Activity Recognition","created":"2021-08-17","cited_by_count":1,"area":null},{"id":"2207.08187","title":"Federated Self-Supervised Learning in Heterogeneous Settings: Limits of a Baseline Approach on HAR","created":"2022-07-17","cited_by_count":1,"area":null},{"id":"2209.12046","title":"Blinder: End-to-end Privacy Protection in Sensing Systems via Personalized Federated Learning","created":"2022-09-24","cited_by_count":1,"area":null},{"id":"2301.01838","title":"PMP: Privacy-Aware Matrix Profile against Sensitive Pattern Inference for Time Series","created":"2023-01-04","cited_by_count":1,"area":null},{"id":"2303.04636","title":"Robust Multimodal Fusion for Human Activity Recognition","created":"2023-03-08","cited_by_count":1,"area":null},{"id":"2304.10068","title":"Fruit Picker Activity Recognition with Wearable Sensors and Machine Learning","created":"2023-04-20","cited_by_count":1,"area":null},{"id":"2401.08637","title":"Synergy: Towards On-Body AI via Tiny AI Accelerator Collaboration on Wearables","created":"2023-12-11","cited_by_count":1,"area":null},{"id":"2406.16943","title":"EarDA: Towards Accurate and Data-Efficient Earable Activity Sensing","created":"2024-06-18","cited_by_count":1,"area":null},{"id":"2409.17994","title":"CRoP: Context-wise Robust Static Human-Sensing Personalization","created":"2024-09-26","cited_by_count":1,"area":null},{"id":"2509.24303","title":"Experience Paper: Adopting Activity Recognition in On-demand Food Delivery Business","created":"2025-09-29","cited_by_count":1,"area":null},{"id":"2510.08635","title":"Hi-OSCAR: Hierarchical Open-set Classifier for Human Activity Recognition","created":"2025-10-08","cited_by_count":1,"area":null},{"id":"2602.15379","title":"FlashMem: Supporting Modern DNN Workloads on Mobile with GPU Memory Hierarchy Optimizations","created":"2026-02-17","cited_by_count":1,"area":null},{"id":"2608.15861","title":"TransfHAR: Self-Supervised Wrist Representations for On-Demand Activity Recognition","created":"2026-08-16","cited_by_count":1,"area":null},{"id":"2101.03724","title":"Wheelchair Behavior Recognition for Visualizing Sidewalk Accessibility by Deep Neural Networks","created":"2021-01-11","cited_by_count":0,"area":null},{"id":"2101.04948","title":"Deep State Inference: Toward Behavioral Model Inference of Black-box Software Systems","created":"2021-01-13","cited_by_count":0,"area":null},{"id":"2204.10416","title":"CycleSense: Detecting Near Miss Incidents in Bicycle Traffic from Mobile Motion Sensors","created":"2022-04-21","cited_by_count":0,"area":null},{"id":"2205.11756","title":"UMSNet: An Universal Multi-sensor Network for Human Activity Recognition","created":"2022-05-24","cited_by_count":0,"area":null},{"id":"2205.12225","title":"Psychotic Relapse Prediction in Schizophrenia Patients using A Mobile Sensing-based Supervised Deep Learning Model","created":"2022-05-24","cited_by_count":0,"area":null},{"id":"2208.07643","title":"A Review of the Convergence of 5G/6G Architecture and Deep Learning","created":"2022-08-16","cited_by_count":0,"area":null},{"id":"2211.12776","title":"Research on Data Fusion Algorithm Based on Deep Learning in Target Tracking","created":"2022-11-23","cited_by_count":0,"area":null},{"id":"2303.06048","title":"VALERIAN: Invariant Feature Learning for IMU Sensor-based Human Activity Recognition in the Wild","created":"2023-03-03","cited_by_count":0,"area":null},{"id":"2310.03140","title":"ViFiT: Reconstructing Vision Trajectories from IMU and Wi-Fi Fine Time Measurements","created":"2023-10-04","cited_by_count":0,"area":null},{"id":"2409.16730","title":"Non-stationary BERT: Exploring Augmented IMU Data For Robust Human Activity Recognition","created":"2024-09-25","cited_by_count":0,"area":null},{"id":"2504.00438","title":"Suite-IN++: A FlexiWear BodyNet Integrating Global and Local Motion Features from Apple Suite for Robust Inertial Navigation","created":"2025-04-01","cited_by_count":0,"area":null},{"id":"2506.01962","title":"Graph-Based Adversarial Domain Generalization with Anatomical Correlation Knowledge for Cross-User Human Activity Recognition","created":"2025-05-08","cited_by_count":0,"area":null},{"id":"2510.05840","title":"Multimodal Trajectory Representation Learning for Travel Time Estimation","created":"2025-10-07","cited_by_count":0,"area":null},{"id":"2512.20409","title":"DETACH : Decomposed Spatio-Temporal Alignment for Exocentric Video and Ambient Sensors with Staged Learning","created":"2025-12-23","cited_by_count":0,"area":null},{"id":"2603.10046","title":"Gated Adaptation for Continual Learning in Human Activity Recognition","created":"2026-03-08","cited_by_count":0,"area":null},{"id":"2603.26482","title":"SPECTRA: An Efficient Spectral-Informed Neural Network for Sensor-Based Activity Recognition","created":"2026-03-27","cited_by_count":0,"area":null},{"id":"2605.02743","title":"Triple Spectral Fusion for Sensor-based Human Activity Recognition","created":"2026-05-04","cited_by_count":0,"area":null},{"id":"2605.14014","title":"Dywave: Event-Aligned Dynamic Tokenization for Heterogeneous IoT Sensing Signals","created":"2026-05-13","cited_by_count":0,"area":null},{"id":"2605.15252","title":"PDRNN: Modular Data-driven Pedestrian Dead Reckoning on Loosely Coupled Radio- and Inertial-Signalstreams","created":"2026-05-14","cited_by_count":0,"area":null},{"id":"2605.22086","title":"GenHAR: Generalizing Cross-domain Human Activity Recognition for Last-mile Delivery","created":"2026-05-21","cited_by_count":0,"area":null},{"id":"2608.08439","title":"FSTC-Encoder: Feature--Spatial--Temporal Correlation Learning for Generalizable RF Sensing","created":"2026-08-09","cited_by_count":0,"area":null}],"next_cursor":null}