A comprehensive approach to detecting chemical adulteration in fruits using computer vision, deep learning, and chemical sensors.
Abdus SattarMd. Asif Mahmud RidoyAloke Kumar SahaHafiz Md. Hasan BabuMohammad Nurul HudaPublished in: Intell. Syst. Appl. (2024)
Keyphrases
- deep architectures
- deep learning
- computer vision
- unsupervised learning
- machine learning
- unsupervised feature learning
- pattern recognition
- object recognition
- weakly supervised
- image sequences
- pairwise
- viewpoint
- object detection
- restricted boltzmann machine
- data sets
- multiscale
- natural language
- decision support system
- bayesian networks
- mental models
- decision making