COCM: Co-Occurrence-Based Consistency Matching in Domain-Adaptive Segmentation

This paper focuses on domain adaptation in a semantic segmentation task. Traditional methods regard the source domain and the target domain as a whole, and the image matching is determined by random seeds, leading to a low degree of consistency matching between domains and interfering with the reduction in the domain gap. Therefore, we designed a two-step, three-level cascaded domain consistency matching strategy—co-occurrence-based consistency matching (COCM)—in which the two steps are: Step 1, in which we design a matching strategy from the perspective of category existence and filter the sub-image set with the highest degree of matching from the image of the whole source domain, and Step 2, in which, from the perspective of spatial existence, we propose a method of measuring the PIOU score to quantitatively evaluate the spatial matching of co-occurring categories in the sub-image set and select the best-matching source image. The three levels mean that in order to improve the importance of low-frequency categories in the matching process, we divide the categories into three levels according to the frequency of co-occurrences between domains; these three levels are the head, middle, and tail levels, and priority is given to matching tail categories. The proposed COCM maximizes the category-level consistency between the domains and has been proven to be effective in reducing the domain gap while being lightweight. The experimental results on general datasets can be compared with those of state-of-the-art (SOTA) methods

COCM: Co-Occurrence-Based Consistency Matching in Domain-Adaptive Segmentation

This paper focuses on domain adaptation in a semantic segmentation task. Traditional methods regard the source domain and the target domain as a whole, and the image matching is determined by random seeds, leading to a low degree of consistency matching between domains and interfering with the reduction in the domain gap. Therefore, we designed a two-step, three-level cascaded domain consistency matching strategy—co-occurrence-based consistency matching (COCM)—in which the two steps are: Step 1, in which we design a matching strategy from the perspective of category existence and filter the sub-image set with the highest degree of matching from the image of the whole source domain, and Step 2, in which, from the perspective of spatial existence, we propose a method of measuring the PIOU score to quantitatively evaluate the spatial matching of co-occurring categories in the sub-image set and select the best-matching source image. The three levels mean that in order to improve the importance of low-frequency categories in the matching process, we divide the categories into three levels according to the frequency of co-occurrences between domains; these three levels are the head, middle, and tail levels, and priority is given to matching tail categories. The proposed COCM maximizes the category-level consistency between the domains and has been proven to be effective in reducing the domain gap while being lightweight. The experimental results on general datasets can be compared with those of state-of-the-art (SOTA) methods

Mutation of 4-coumarate: coenzyme A ligase 1 gene affects lignin biosynthesis and increases the cell wall digestibility in maize brown midrib5 mutants

Abstract Background Maize brown midrib (bm) mutants associated with impaired lignin biosynthesis are a potential source for the breed of novel germplasms with improved cell wall digestibility. The spontaneous bm5 mutants had been identified since 2008. However, the gene responsible for the bm5 locus, and the comprehensive effects of bm5 mutation on lignin biosynthesis, soluble phenolics accumulation, and cell wall degradation have yet to be elucidated. Results The bm5 locus was identified to encode a major 4-coumarate: coenzyme A ligase (Zm4CL1) through analyzing MutMap-assisted gene mapping data. Two alleles of Zm4CL1 isolated from bm5 mutants contained two transposons inserted in the first exon and the second intron, respectively, and consequently, the activities of 4CLs in the crude enzyme extracts from bm5 midribs were reduced by 51–62% compared with the wild type. Furthermore, five 4CLs were retrieved from maize genome, and Zm4CL1 was the most highly expressed one in the lignified tissues. Mutation of Zm4CL1 mainly impeded the biosynthesis of guaiacyl (G) lignins and increased the level of soluble feruloyl derivatives without impacting maize growth and development. Moreover, both neutral detergent fiber digestibility and saccharification efficiency of cell walls were significantly elevated in the bm5 mutant. Conclusions Zm4CL1 was identified as the Bm5 gene, since two independent alleles of Zm4CL1 were associated with the same mutant phenotype. Mutation of Zm4CL1 mainly affected G lignin biosynthesis and soluble feruloyl derivatives accumulation in maize lignified tissues. The reduced recalcitrance of the bm5 mutant suggests that Zm4CL1 is an elite target for cell wall engineering, and genetic manipulation of this gene will facilitate the utilization of crop straw and stover that have to be dealt with for environmental protection