|
|
|
|
|
Dario Macaluso, Francesco Licciardo and Katya Carbone
In recent years, the primary sector in Italy and elsewhere has been profoundly affected by climate change and a deep economic crisis, mainly linked to stagnating prices and rising production costs. Because of this situation, we are witnessing renewed int...
ver más
|
|
|
|
|
|
|
|
|
Jun Tie, Weibo Wu, Lu Zheng, Lifeng Wu and Ting Chen
When aiming at the problems such as missed detection or misdetection of recognizing green walnuts in the natural environment directly by using target detection algorithms, a method is proposed based on improved UNet3+ for green walnut image segmentation,...
ver más
|
|
|
|
|
|
|
|
|
Che-Hao Chang, Jason Lin, Jia-Wei Chang, Yu-Shun Huang, Ming-Hsin Lai and Yen-Jen Chang
Recently, data-driven approaches have become the dominant solution for prediction problems in agricultural industries. Several deep learning models have been applied to crop yield prediction in smart farming. In this paper, we proposed an efficient hybri...
ver más
|
|
|
|
|
|
|
|
|
Sellaperumal Pazhanivelan, N. S. Sudarmanian, Vellingiri Geethalakshmi, Murugesan Deiveegan, Kaliaperumal Ragunath, A. P. Sivamurugan and P. Shanmugapriya
Synthetic aperture radar (SAR) imagery, notably Sentinel-1A?s C-band, VV, and VH polarized SAR, has emerged as a crucial tool for mapping rice fields, especially in regions where cloud cover hinders optical imagery. Employing multi-temporal characteristi...
ver más
|
|
|
|
|
|
|
|
|
Maksym W. Sitnicki, Nataliia Prykaziuk, Humeniuk Ludmila, Olena Pimenowa, Florin Imbrea, Laura ?muleac and Raul Pa?calau
The digitalization of the agricultural industry is manifested through the active use of innovative technologies in all its areas. Agribusiness owners have to constantly improve their security to meet new challenges. In this context, the existing cyber ri...
ver más
|
|
|
|