Analysing and Applying Captured Object with Machine Learning Techniques
- Resource Type
- Conference
- Authors
- Khan, Soumya Suvra; Majumdar, Rana; Maut, Partha Pratim; Ghosh, Anupam; Mishra, Ved P
- Source
- 2019 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE) Computational Intelligence and Knowledge Economy (ICCIKE), 2019 International Conference on. :287-290 Dec, 2019
- Subject
- Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Computing and Processing
Robotics and Control Systems
Transportation
Object detection
Computer vision
Gesture recognition
Training
Task analysis
Cameras
Real-time systems
Objection detection
computer vision
Machine learning
Gesture Analysis
- Language
Detecting an object either form a static or dynamic image is considered to be a fundamental objective in the area of a computer vision. Object detection techniques can be applied both to static images as well as for dynamic images. Presently there subsist implementations of applications that uses object detection; this work orients itself on object detection using artificial intelligence and machine learning techniques implementing varied computer vision characteristics. The aim is to integrate state-of-the-art practice for object recognition with the intension of attaining extraordinary accurateness with an instantaneous enactment. The basic working is to identify patterns while capturing objects using camera to identify different daily tasks-and implementing them using gesturing. The final result exhibits real-time performance and satisfactory toning outcomes.