Luo et al., 2015 - Google Patents
Gaussian successive fuzzy integral for sequential multi-decision makingLuo et al., 2015
- Document ID
- 14930703477125156846
- Author
- Luo A
- Chen S
- Fang C
- Publication year
- Publication venue
- International Journal of Fuzzy Systems
External Links
Snippet
Fuzzy integral provides a powerful tool for fusing multiple sources of information or evidence to give an evaluation that expresses the level of confidence (or preference) in a particular hypothesis (or decision). However, the computational framework of the fuzzy integral is not …
- 238000011156 evaluation 0 abstract description 3
Classifications
-
- 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
- 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
- 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
-
- 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
- G06N7/00—Computer systems based on specific mathematical models
-
- 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
- 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
- G06Q10/06—Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
-
- 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
-
- 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
- G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
-
- 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
- G06K9/6279—Classification techniques relating to the number of classes
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Chen et al. | Use of sequential learning for short-term traffic flow forecasting | |
US7523079B2 (en) | Situation dependent operation of a semantic network machine | |
Fakhri et al. | A fuzzy decision-making system for video tracking with multiple objects in non-stationary conditions | |
Louati | A hybridization of deep learning techniques to predict and control traffic disturbances | |
Skowron et al. | Complex patterns | |
Gupta et al. | Accident detection using time-distributed model in videos | |
Darias et al. | Using case-based reasoning for capturing expert knowledge on explanation methods | |
Kuwertz et al. | Applying knowledge-based reasoning for information fusion in intelligence, surveillance, and reconnaissance | |
Matez-Bandera et al. | Efficient semantic place categorization by a robot through active line-of-sight selection | |
Li | Advances in deep reinforcement learning for computer vision applications | |
Dhevanandhini et al. | An optimal intelligent video surveillance system in object detection using hybrid deep learning techniques | |
Albusac et al. | Intelligent surveillance based on normality analysis to detect abnormal behaviors | |
Tank et al. | Synchronization, optimization, and adaptation of machine learning techniques for computer vision in Cyber-Physical Systems: a comprehensive analysis | |
Salfinger et al. | Maintaining Situation Awareness over Time--A Survey on the Evolution Support of Situation Awareness Systems | |
Chiappino et al. | Event based switched dynamic bayesian networks for autonomous cognitive crowd monitoring | |
Luo et al. | Gaussian successive fuzzy integral for sequential multi-decision making | |
Mohan et al. | Predictive temporal data-mining approach for evolving knowledge based reservoir operation rules | |
Lim et al. | Object detection in autonomous vehicles: A performance analysis | |
Albusac et al. | Monitoring Complex Environments Using a Knowledge-Driven Approach Based on Intelligent Agents. | |
Priyanka et al. | Deep learning based video surveillance for predicting vehicle density in real time scenario | |
Lei et al. | Interpretable Fuzzy Granular Reasoning Framework for Industrial Dynamic Complex Event Recognition | |
Zhang | RETRACTED ARTICLE: Evaluation of image segmentation and multi class object recognition algorithm based on machine learning | |
Ammour et al. | Scene analysis using both a probabilistic evolutionary graph and the evidence theory | |
Robertson et al. | Automatic human behaviour recognition and explanation for CCTV video surveillance | |
Das et al. | DriCon: On-device just-in-time context characterization for unexpected driving events |