D. Lorente

TL;DR: The different technologies available to acquire the images and their use for the non-destructive inspection of the internal and external features of these products are explained, with details of the statistical techniques most commonly used for this task.

TL;DR: This work proposes a methodology to select features in multi-class classification problems using the receiver operating characteristic curve, in order to detect rottenness in citrus fruits by means of hyperspectral images.

TL;DR: In this article, the pericarp of mangos at different stages of ripeness was evaluated based on the analysis of hyperspectral images, and a 97.9% rate was achieved on the third day after the damage had been caused using k-Nearest Neighbours and the whole spectra.

TL;DR: A data-driven method to simulate, in real-time, the biomechanical behavior of the breast tissues in some image-guided interventions such as biopsies or radiotherapy dose delivery as well as to speed up multimodal registration algorithms.

TL;DR: In this article, the feasibility of reflectance spectroscopy in the visible and near infrared (NIR) regions was evaluated for the automatic detection of the early symptoms of decay caused by Penicillium digitatum fungus in citrus fruit.