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Object Recognition Through Smartphone Using Deep Learning Techniques
- Source :
- Soft Computing Systems ISBN: 9789811319358
- Publication Year :
- 2018
- Publisher :
- Springer Singapore, 2018.
-
Abstract
- Object recognition technology has matured to a point at which exciting applications have become possible. Indeed, industry has created a variety of computer vision products and services from the traditional area of machine inspection to more recent applications such as object detection, video surveillance, or face recognition. This paper is about achieving the goal of object recognition through advanced techniques like deep learning on handy devices like smartphones and tablets. Deep learning algorithms (Convolutional Neural Networks (CNN)) are used for the primary aim of object recognition. Images are clicked through the camera of the smartphone during experimentation and are fed to the CNN network. The top four results predicted by the network are depicted on the smartphone screen in the audio and the visual form i.e. predicted object name and the probability of predicted object being the one actually clicked in the decreasing order of probabilities. The accuracy obtained in object recognition is about 93% through the application.
- Subjects :
- Point (typography)
business.industry
Computer science
Deep learning
0206 medical engineering
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Cognitive neuroscience of visual object recognition
02 engineering and technology
Object (computer science)
020601 biomedical engineering
Facial recognition system
Convolutional neural network
Object detection
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Computer vision
Artificial intelligence
business
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- Soft Computing Systems ISBN: 9789811319358
- Accession number :
- edsair.doi...........19b36ceab6009cc46fa7937685bad524