PLLaMa: An Open-source Large Language Model for Plant Science

1 code implementation • 3 Jan 2024 • Xianjun Yang, Junfeng Gao, Wenxin Xue, Erik Alexandersson

Large Language Models (LLMs) have exhibited remarkable capabilities in understanding and interacting with natural language across various sectors.

Language Modelling Large Language Model

Transferring learned patterns from ground-based field imagery to predict UAV-based imagery for crop and weed semantic segmentation in precision crop farming

no code implementations • 20 Oct 2022 • Junfeng Gao, Wenzhi Liao, David Nuyttens, Peter Lootens, Erik Alexandersson, Jan Pieters

The results show that the mean intersection of union (IOU) values of the segmentation for the crop (maize), weeds, and soil background in the developed model for the field dataset are 0. 744, 0. 577, 0. 979, respectively, and the performance of aerial images from an UAV with the same model, the IOU values of the segmentation for the crop (maize), weeds and soil background are 0. 596, 0. 407, and 0. 875, respectively.

Segmentation Semantic Segmentation

In-field early disease recognition of potato late blight based on deep learning and proximal hyperspectral imaging

no code implementations • 23 Nov 2021 • Chao Qi, Murilo Sandroni, Jesper Cairo Westergaard, Ea Høegh Riis Sundmark, Merethe Bagge, Erik Alexandersson, Junfeng Gao

Effective early detection of potato late blight (PLB) is an essential aspect of potato cultivation.