Verfahren und System zur Erzeugung von Räumlich-Zeitlichen Intercrop-Layouts unter Verwendung eines 3D-Cnn-Lstm-Basierten Grosssichtmodells

Details

Veröffentlichungs-Nr.

EP4730275

Anmeldetag

19. September 2025

Veröffentlichung

22. April 2026

Rechtsraum

EP

Abstract

This disclosure relates generally to method and system to generate spatio-temporal intercrop layouts using 3D-CNN-LSTM based large vision model. The method is a pretrained spatio-temporal crop interaction model based on a 3D-CNN-LSTM to recommend optimal intercrop combinations. The method initially receives a user request as input which is preprocessed by removing noise and performing normalization. Further, a pretrained 3D-CNN-LSTM model is utilized to generate an optimal spatio-temporal intercrop layout for each intercropping scenario. The method also provides providing dynamic visual insight for the spatio-temporal intercrop layout comprising crop growth and corresponding intercrop interaction. Finally, an user feedback is obtained from at least one of the user or non-invasively in response to the user request for iterative improvements and fine-tuning the 3D-CNN-LSTM model using reinforcement learning.

Anmelder

Firma

Tata Consultancy Services Limited

Land

🇮🇳 Indien