ROOM 3 PLENARY TALK Prof  Daniel Ulises Campos Delgado, PhD  Title   Hybrid Classification Approach
Channel: Cinvestav - Ingeniería Eléctrica
Date: 2022-11-15

"Hybrid Classification Approach for Correlated Multimodality Images: Unmixing Processing + Artificial Intelligence"
Abstract 
Correlated multimodal images allow to capture spatial-temporal or spatial-spectral information simultaneously from a scene. These types of images had found applications in diverse fields, as earth observation to identify types of vegetation, medical diagnosis to detect cancerous lesions in the skin or oral cavity, food inspection to distinguish contaminants, non-destructive testing to perceive defects in materials, among others. One of the main challenges in this field is to make an efficient and fast processing of the vast acquired information. In this talk, I will focus on the classification problem of correlated multimodal images by a hybrid approach. Hence, first, linear and nonlinear unmixing are used to extract features to guide the classification process by applying the algorithm “extended blind end-member and abundance extraction”, which was developed by our research team. Next, machine learning and deep learning are applied to achieve the final pixel labeling. In the talk, I will focus on the applications to medical diagnosis and non-destructive testing for our hybrid classification approach.