Abstract: Aiming at the challenges of high intra-class disparity and low inter-class disparity in fine-grained image classification, a multi-branch fine-grained image classification method based on ...

Abstract: As one of the core tasks in vision recognition, image classification is widely used in various scenarios. Most existing mainstream image classification models use the Convolutional Neural ...

Beans are a legume that is widely grown and consumed globally, being the staple food for humans in developing countries. Nitrogen (N) is the most limiting nutrient for yield and foliar analysis is ...

Classifying corn varieties presents a significant challenge due to the high-dimensional characteristics of hyperspectral images and the complexity of feature extraction, which hinder progress in ...

This project was developed as part of my Master's programm at Heilbronn University. The goal is to classify different oil samples (e.g. olive oil, sunflower oil) based on their fluorescence and ...

Introduction: A novel classification scheme for endplate lesions, based on T2-weighted images from magnetic resonance imaging (MRI) scan, has been recently introduced and validated. The scheme ...

This Annotation Framework involves in identifying and recognising the objects within the given image using predefined neural network learning algorithms and tools.