The demand for intelligent agriculture is increasing due to the continuous impact of world
food and environmental crises. Focusing on fruit detection, with the rapid development of …

Fruit detection and localization are essential for future agronomic management of fruit crops
such as yield prediction, yield map** and automated harvesting. However, to perform …

Highlights•A method for rapid and accurate apple fruitlet detection before fruit thinning is
proposed.•The method is based on a state-of-the-art deep learning approach.•The model …

Deep learning has demonstrated excellent capabilities for learning image features and is
widely used in image object detection. In order to improve the performance of machine …

It is important to precisely segment apples in an orchard during the growth period to obtain
accurate growth information. However, the complex environmental factors and growth …

With being rapid increasing population in worldwide, the need for satisfactory level of crop
production with decreased amount of agricultural lands. Machine vision would ensure the …

A machine vision system for detecting apples in orchards was developed. The system was
designed to be used in harvesting robots and is based on a YOLOv3 algorithm with special …

This paper reviews the research and development of machine vision systems for fruit
detection and localization for robotic harvesting and/or crop-load estimation of specialty tree …

This review reports the recent state of the art in the field of mobile robots applied to precision
agriculture. After a brief introduction to precision agriculture, the review focuses on two main …

Every apple destined for the fresh market is picked by the human hand. Despite extensive
research over the past four decades, there are no mechanical apple harvesters for the fresh …