[go: up one dir, main page]

Savitz et al., 2023 - Google Patents

Edge analytics on resource constrained devices

Savitz et al., 2023

View PDF
Document ID
4890378049011976389
Author
Savitz S
Perera C
Rana O
Publication year
Publication venue
International Journal of Computational Science and Engineering

External Links

Snippet

Camera sensors can measure our environment at high precision, providing the basis for detecting more complex phenomena in comparison to other sensors, eg, temperature or humidity. Using benchmarks, this work evaluates object classification on resource …
Continue reading at orca.cardiff.ac.uk (PDF) (other versions)

Classifications

    • 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
    • G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46—Extraction of features or characteristics of the image
    • 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
    • G06K9/62—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
    • 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
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
    • 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
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • 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
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computer systems utilising knowledge based models
    • 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

Similar Documents

Publication Publication Date Title
Murthy et al. ObjectDetect: A Real‐Time Object Detection Framework for Advanced Driver Assistant Systems Using YOLOv5
WO2022083536A1 (en) Neural network construction method and apparatus
Khosravi et al. Crowd emotion prediction for human-vehicle interaction through modified transfer learning and fuzzy logic ranking
CN113807399A (en) Neural network training method, neural network detection method and neural network detection device
CN115424237B (en) Forward vehicle identification and distance detection method based on deep learning
CN116935188B (en) Model training method, image recognition method, device, equipment and medium
CN116432736A (en) Neural network model optimization method, device and computing equipment
Mishra et al. Sensing accident-prone features in urban scenes for proactive driving and accident prevention
Wang et al. A small object detection model in aerial images based on CPDD-YOLOv8
Qian et al. TSDet: A new method for traffic sign detection based on YOLOv5‐SwinT
CN115905450A (en) Unmanned aerial vehicle monitoring-based water quality abnormity tracing method and system
WO2023184188A1 (en) Method and apparatus for fault monitoring of neural network model in autonomous driving system
Nesen et al. Knowledge graphs for semantic-aware anomaly detection in video
WO2024220270A1 (en) Systems and methods for generating model architectures for task-specific models in accelerated transfer learning
Sanjai Siddharthan et al. Real-time road hazard classification using object detection with deep learning
Namana et al. Enhancing Surveillance Systems leveraging AIoT for Advanced Object Detection in Real-Time Security Applications
Savitz et al. Edge analytics on resource constrained devices
Asif et al. Performance Evaluation of Deep Learning Algorithm Using High‐End Media Processing Board in Real‐Time Environment
CN116524314A (en) Unmanned aerial vehicle small target detection method based on anchor-free frame algorithm
El Mallahi et al. A Distributed Big Data Analytics Model for Traffic Accidents Classification and Recognition based on SparkMlLib Cores.
Wu et al. Advancing construction safety: YOLOv8-CGS helmet detection model
Wu et al. Channel‐wise attention model‐based fire and rating level detection in video
Zhang et al. Latte: Lightweight attention-based traffic accident anticipation engine
Chen et al. A study on a target detection model for autonomous driving tasks
CN116824127A (en) Open world target detection method, computer device, and storage medium