Building expert systems
Introduction to artificial neural systems
Introduction to artificial neural systems
Artificial intelligence: a modern approach
Artificial intelligence: a modern approach
Machine Learning
Introduction to Expert Systems
Introduction to Expert Systems
Machine Learning
Machine Learning
An introduction to variable and feature selection
The Journal of Machine Learning Research
The Interplay of Optimization and Machine Learning Research
The Journal of Machine Learning Research
An empirical evaluation of supervised learning in high dimensions
Proceedings of the 25th international conference on Machine learning
| Hi-index | 0.00 |
Vine pruning is an important part of vineyard management, and pruning is the most expensive task in the vineyard which has not yet been automated. Every year, most new canes must be removed from the vine, and the choice of canes to retain impacts vine yield. To automate the process of vine pruning, a vine pruning robot must make decisions on what canes to remove or to keep, based on a 3D topological model of the structure of the vine. In this paper we present an Artificial Intelligence (AI) system for making these decisions, developed and evaluated using simulated vines. A viticulture expert evaluated our approach by comparing it to pruning decisions made by a pruner with a skill level typical of human pruners. Our system successfully pruned 30% of vines better than the human and 89% at least as well. These results demonstrate that the vine pruning problem is solvable using current computing technologies, and that automating the pruning process has the potential to improve vine quality and yield.