MSc thesis topic: UAV-based grape cluster detection and extraction of features with agronomical interest with multispectral and thermal images using Deep Learning and ArtificialIntelligence
UAVs have enabled a great revolution in agriculture due to the important reduction in costs they present, together with a rapid data acquisition. The combination of UAV data with Artificial Intelligence and Deep Learning has provided the farmer with new tools to know the state of the crop in more detail.
The identification of grape clusters and the estimation of their dimensions, among many other relevant features, are of importance for the estimation of the yield and the quality of it. Therefore, being able to know these features in advance can prepare the farmer with useful information about the status of the vineyard and the income to be received at the end of the campaign.
Relevance to research/projects
- Analyze the importance of multispectral and thermal imagery for grape clusters detection
- Train an algorithm that allows the detection of grape clusters (masks) in images
- Extract features with agronomical interests from the masks detected
- Santos, T. T., de Souza, L. L., dos Santos, A. A., & Avila, S. (2020). Grape detection, segmentation, and tracking using deep neural networks and three-dimensional association. Computers and Electronics in Agriculture, 170, 105247.
- Grant, O. M., Ochagavía, H., Baluja, J., Diago, M. P., & Tardáguila, J. (2016). Thermal imaging to detect spatial and temporal variation in the water status of grapevine (Vitis viniferaL.). The Journal of Horticultural Science and Biotechnology, 91(1), 43–54.
- Sa, I., Ge, Z., Dayoub, F., Upcroft, B., Perez, T., & McCool, C. (2016). Deepfruits: A fruit detection system using deep neural networks. Sensors, 16(8), 1222.
- Stein, M., Bargoti, S., & Underwood, J. (2016). Image based mango fruit detection, localisation and yield estimation using multiple view geometry. Sensors, 16(11), 1915.
- UAV enthusiast
- Willing work with AI and DL
- Excited to work with high-tech platforms
Theme(s): Sensing & measuring