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Artificial Intelligence of Things: A Survey
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Ethics of the health-related internet of things: a narrative review
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Deep Learning for IoT Big Data and Streaming Analytics: A Survey
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Deep Learning in Mobile and Wireless Networking: A Survey
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Collaborative Sensing in Internet of Things: A Comprehensive Survey
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Enabling Resource-Efficient AIoT System With Cross-Level Optimization: A Survey
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2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
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TimelyFL: Heterogeneity-aware Asynchronous Federated Learning with Adaptive Partial Training
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GPT-FL: Generative Pre-Trained Model-Assisted Federated Learning
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2003 IEEE International Conference on Acoustics, Speech, and Signal Processing ICASSP '03
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Adaptive Quantization of Model Updates for Communication-Efficient Federated Learning
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FedAudio: A Federated Learning Benchmark for Audio Tasks
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A Distributed Synchronous SGD Algorithm with Global Top-k Sparsification for Low Bandwidth Networks
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2021 IEEE 41st International Conference on Distributed Computing Systems (ICDCS)
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MandiPass: Secure and Usable User Authentication via Earphone IMU
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Personalized Federated Learning by Structured and Unstructured Pruning under Data Heterogeneity
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Is LoRaWAN Really Wide? Fine-grained LoRa Link-level Measurement in An Urban Environment
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DeepLoRa: Learning Accurate Path Loss Model for Long Distance Links in LPWAN
inferredcites →https://doi.org/10.1109/iotm.004.2100182openalex-snapshot
Federated Learning for the Internet of Things: Applications, Challenges, and Opportunities
inferredcites →https://doi.org/10.1109/ipsn.2016.7460664openalex-snapshot
DeepX: A Software Accelerator for Low-Power Deep Learning Inference on Mobile Devices
inferredcites →https://doi.org/10.1109/ipsn.2018.00051openalex-snapshot
ODDS: Real-Time Object Detection Using Depth Sensors on Embedded GPUs
inferredcites →https://doi.org/10.1109/ipsn48710.2020.00-26openalex-snapshot
CollabAR: Edge-assisted Collaborative Image Recognition for Mobile Augmented Reality
inferredcites →https://doi.org/10.1109/ipsn48710.2020.00-51openalex-snapshot
Supreme: Fine-grained Radio Map Reconstruction via Spatial-Temporal Fusion Network
inferredcites →https://doi.org/10.1109/ipsn54338.2022.00014openalex-snapshot
SPARCS: A Sparse Recovery Approach for Integrated Communication and Human Sensing in mmWave Systems
inferredcites →https://doi.org/10.1109/ipsn54338.2022.00016openalex-snapshot
Individualizing Head-Related Transfer Functions for Binaural Acoustic Applications
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FaceListener: Recognizing Human Facial Expressions via Acoustic Sensing on Commodity Headphones
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Vi-Fi: Associating Moving Subjects across Vision and Wireless Sensors
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inferredcites →https://doi.org/10.1109/ipsn54338.2022.00029openalex-snapshot
BalanceFL: Addressing Class Imbalance in Long-Tail Federated Learning
inferredcites →https://doi.org/10.1109/ipsn54338.2022.00030openalex-snapshot
YONO: Modeling Multiple Heterogeneous Neural Networks on Microcontrollers
inferredcites →https://doi.org/10.1109/jiot.2020.3039359openalex-snapshot
Empowering Things With Intelligence: A Survey of the Progress, Challenges, and Opportunities in Artificial Intelligence of Things
inferredcites →https://doi.org/10.1109/jiot.2021.3088875openalex-snapshot
A Survey of Recent Advances in Edge-Computing-Powered Artificial Intelligence of Things
inferredcites →https://doi.org/10.1109/jsac.2021.3118435openalex-snapshot
FedSA: A Semi-Asynchronous Federated Learning Mechanism in Heterogeneous Edge Computing
inferredcites →https://doi.org/10.1109/mic.2024.3443169openalex-snapshot
The Internet of Things in the Era of Generative AI: Vision and Challenges
inferredcites →https://doi.org/10.1109/sec50012.2020.00014openalex-snapshot
FlexDNN: Input-Adaptive On-Device Deep Learning for Efficient Mobile Vision
inferredcites →https://doi.org/10.1109/sensys-ml62579.2024.00007openalex-snapshot
LLMSense: Harnessing LLMs for High-level Reasoning Over Spatiotemporal Sensor Traces
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Spatio-temporal spectral analysis by eigenstructure methods
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SAFA: A Semi-Asynchronous Protocol for Fast Federated Learning With Low Overhead
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showing the first 200 of 338 · page through all 338
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Incoming claims: where this work appears in other papers’ reference lists and arguments.
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inferred← citeshttps://doi.org/10.32604/cmc.2025.066241openalex-snapshot
FedEPC: An Efficient and Privacy-Enhancing Clustering Federated Learning Method for Sensing-Computing Fusion Scenarios
inferred← citeshttps://doi.org/10.32725/978-80-7694-143-4.20openalex-snapshot
Artificial Intelligence in Small and Medium-Sized Companies - Comparative Analysis of V4 Region
inferred← citeshttps://doi.org/10.3390/app16136787openalex-snapshot
AgentProphet: Source-Aware Multi-Agent Emerging Technology Forecasting for Upstream Decision-Making in AI-Based IoT Systems
inferred← citeshttps://doi.org/10.3390/drones9090605openalex-snapshot
Real-Time Vision–Language Analysis for Autonomous Underwater Drones: A Cloud–Edge Framework Using Qwen2.5-VL
inferred← citeshttps://doi.org/10.3390/fi18060296openalex-snapshot
Distributed Intelligence in the Artificial Intelligence of Things: A Review of Artificial Intelligence Workload Placement Across the Device-Edge-Fog-Cloud Continuum
inferred← citeshttps://doi.org/10.3390/iot6030048openalex-snapshot
A Two-Stage Hybrid Federated Learning Framework for Privacy-Preserving IoT Anomaly Detection and Classification
inferred← citeshttps://doi.org/10.3390/su18168073openalex-snapshot
Artificial Intelligence of Things (AIoT) in Smart Farming: A Bibliometric Analysis and Future Research Agenda
inferred← citeshttps://doi.org/10.4018/979-8-3373-7046-0.ch006openalex-snapshot
Opportunities and Future Directions in AI Inference for IoT
inferred← citeshttps://doi.org/10.4018/979-8-3693-8512-8.ch001openalex-snapshot
Artificial Intelligence of Things (AIoT)
inferred← citeshttps://doi.org/10.4018/979-8-3693-8547-0.ch012openalex-snapshot
Revolutionising Agriculture
inferred← citeshttps://doi.org/10.4018/ijwltt.409365openalex-snapshot
Accurate Calibration of Physical Education Teaching Action Based on Artificial Intelligence Deep Learning Technology
inferred← citeshttps://doi.org/10.47447/tjsm.0939openalex-snapshot
Patient Expectations Regarding High-Quality Anterior Cruciate Ligament (ACL) Surgery Videos
inferred← citeshttps://doi.org/10.53623/gisa.v5i2.706openalex-snapshot
A Systematic Literature Review of YOLO and IoT Applications in Smart Waste Management
inferred← citeshttps://doi.org/10.55643/fcaptp.5.64.2025.4953openalex-snapshot
BASIC PILLARS OF THE INDUSTRIAL-DIGITAL TECHNOLOGICAL ORDER
inferred← citeshttps://doi.org/10.55905/cuadv17n12-047openalex-snapshot
Aquicultura de precisão: uma revisão sobre soluções de monitoramento em tempo real com o uso de IoT e sensores
inferred← citeshttps://doi.org/10.63456/aamc-2-2-51openalex-snapshot
BROADBAND DIPOLE ANTENNA WITH INTEGRATED BALUN FOR ENHANCED WIDEBAND AND STABLE COMMUNICATION PERFORMANCE
inferred← citeshttps://doi.org/10.64628/aak.jhagttntdopenalex-snapshot
L’« IA edge », qu’est-ce que c’est et à quoi ça sert ?
inferred← citeshttps://doi.org/10.64628/aak.mekcwepcmopenalex-snapshot
What is ‘Edge AI’? What does it do and what can be gained from this alternative to cloud computing?
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
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