Fusing multimodal environmental data for agricultural inference

Abstract

Implementations are disclosed for fusing multiple modalities of data into a multimodal feature embedding and then processing the multimodal feature embedding using various downstream processes for training and/or inference purposes. In various implementations, multiple different modalities of agricultural data about an agricultural parcel may be obtained. Each modality of agricultural data may be processed based on a respective modality-specific encoder to generate a respective modality-specific embedding. The plurality of modality-specific embeddings may be processed based on a multimodal fusion machine learning model to generate a multimodal feature embedding that represents the agricultural parcel. In some implementations, the multimodal feature embedding may be processed using downstream computer process(es) to generate agricultural prediction(s) about the agricultural parcel. Additionally or alternatively, the multimodal feature embedding may be used to train the multimodal fusion model and/or the modality specific encoder(s).