Jiang et al., 2019 - Google Patents
Distributed deep learning optimized system over the cloud and smart phone devicesJiang et al., 2019
- Document ID
- 7782961874409501287
- Author
- Jiang H
- Starkman J
- Lee Y
- Chen H
- Qian X
- Huang M
- Publication year
- Publication venue
- IEEE Transactions on Mobile Computing
External Links
Snippet
Deep learning has been becoming a promising focus in data mining research. With deep learning techniques, researchers can discover deep properties and features of events from quantitative mobile sensor data. However, many data sources are geographically separated …
- 238000000034 method 0 abstract description 19
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/02—Computer systems based on biological models using neural network models
- G06N3/04—Architectures, e.g. interconnection topology
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
- G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for programme control, e.g. control unit
- G06F9/06—Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
- G06F9/46—Multiprogramming arrangements
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
- G06F19/34—Computer-assisted medical diagnosis or treatment, e.g. computerised prescription or delivery of medication or diets, computerised local control of medical devices, medical expert systems or telemedicine
- G06F19/345—Medical expert systems, neural networks or other automated diagnosis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computer systems utilising knowledge based models
- G06N5/04—Inference methods or devices
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computer systems utilising knowledge based models
- G06N5/02—Knowledge representation
- G06N5/022—Knowledge engineering, knowledge acquisition
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F15/00—Digital computers in general; Data processing equipment in general
- G06F15/16—Combinations of two or more digital computers each having at least an arithmetic unit, a programme unit and a register, e.g. for a simultaneous processing of several programmes
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N7/00—Computer systems based on specific mathematical models
- G06N7/005—Probabilistic networks
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6267—Classification techniques
- G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Bharathi et al. | Energy efficient clustering with disease diagnosis model for IoT based sustainable healthcare systems | |
Shynu et al. | Blockchain-based secure healthcare application for diabetic-cardio disease prediction in fog computing | |
Xu et al. | Edge intelligence: Architectures, challenges, and applications | |
Attota et al. | An ensemble multi-view federated learning intrusion detection for IoT | |
Sreedevi et al. | Application of cognitive computing in healthcare, cybersecurity, big data and IoT: A literature review | |
Chen et al. | Deep learning with edge computing: A review | |
Jiang et al. | Distributed deep learning optimized system over the cloud and smart phone devices | |
Liu et al. | Keep your data locally: Federated-learning-based data privacy preservation in edge computing | |
Aouedi et al. | Handling privacy-sensitive medical data with federated learning: challenges and future directions | |
Rajendran et al. | Emphasizing privacy and security of edge intelligence with machine learning for healthcare | |
Xu et al. | A survey on edge intelligence | |
Wang et al. | Deep reinforcement learning-based scheduling for optimizing system load and response time in edge and fog computing environments | |
Presotto et al. | Semi-supervised and personalized federated activity recognition based on active learning and label propagation | |
He et al. | MTAD‐TF: Multivariate Time Series Anomaly Detection Using the Combination of Temporal Pattern and Feature Pattern | |
Wang et al. | A multitask learning-based network traffic prediction approach for SDN-enabled industrial Internet of Things | |
He et al. | Developing an efficient deep learning‐based trusted model for pervasive computing using an LSTM‐based classification model | |
WO2022012668A1 (en) | Training set processing method and apparatus | |
Balaji et al. | Dynamic distributed generative adversarial network for intrusion detection system over internet of things | |
Gajevic et al. | Artificial neural network tuning by improved sine cosine algorithm for healthcare 4.0 | |
Toğaçar | Detecting attacks on IoT devices with probabilistic Bayesian neural networks and hunger games search optimization approaches | |
CU et al. | EHR privacy preservation using federated learning with DQRE-Scnet for healthcare application domains | |
Muazu et al. | A federated learning system with data fusion for healthcare using multi-party computation and additive secret sharing | |
Raza | Secure and privacy-preserving federated learning with explainable artificial intelligence for smart healthcare system | |
Dong et al. | An Autoencoder-based Multi-task Learning for Intrusion Detection in IoT Networks | |
Abidi et al. | Big data-based smart health monitoring system: using deep ensemble learning |