Abstract: A R gene is arranged for controlling soybean-rhizobia compatibility, wherein the GmNNL1 gene of the gene sequence in Hengfeng black bean of the soybean products is shown in SEQ ID NO. 2, and the encoded amino acid sequence is shown in SEQ ID NO. 3. The soybean R gene GmNNL1 is an effective gene that is able to regulate the nodule number of specific rhizobia on soybean, and to regulate the nodule number by directly recognizing the haplotype of the bradyrhizobia-specific effector protein NopP, which is able to limit the symbiotic nodulation of indigenousrhizobia, make soybean preferentially nodule with artificially applied high-efficiency rhizobia agents, and improve symbiotic nitrogen fixation capacity.

Abstract: At least one input image comprising curvilinear features is received. Latent representations of the input images are learned using a trained deep neural network. At least one boundary estimate is determined based on the latent representations. At least one segmentation estimate of the at least one input image is determined based on the latent representations. The at least one image is mapped to output segmentation maps based on the segmentation estimate and the at least one boundary estimate.

Abstract: At least one input image comprising curvilinear features is received. Latent representations of the input images are learned using a trained deep neural network. At least one boundary estimate is determined based on the latent representations. At least one segmentation estimate of the at least one input image is determined based on the latent representations. The at least one image is mapped to output segmentation maps based on the segmentation estimate and the at least one boundary estimate.