Few-Shot Fruit Segmentation via Transfer Learning

arXiv:2405.02556v1 Announce Type: new
Abstract: Advancements in machine learning, computer vision, and robotics have paved the way for transformative solutions in various domains, particularly in agriculture. For example, accurate identification and segmentation of fruits from field images plays a crucial role in automating jobs such as harvesting, disease detection, and yield estimation. However, achieving robust and precise infield fruit segmentation remains a challenging task since large amounts of labeled data are required to handle variations in fruit size, shape, color, …

abstract agriculture arxiv computer computer vision cs.cv cs.ro detection disease domains example few-shot however identification images jobs machine machine learning robotics role segmentation solutions the way transfer transfer learning type via vision