AgriGAN: unpaired image dehazing via a cycle-consistent generative adversarial network for the agricultural plant phenotype.

Artificially extracted agricultural phenotype information exhibits high subjectivity and low accuracy, while the utilization of image extraction information is susceptible to interference from haze. Furthermore, the effectiveness of the agricultural image dehazing method used for extracting such information is limited due to unclear texture details and color representation in the images. To address these limitations, we propose AgriGAN (unpaired image dehazing via a cycle-consistent generative adversarial network) for enhancing the dehazing performance in agricultural plant phenotyping.

Enhanced electron transport and self-similarity in quasiperiodic borophene nanoribbons with line defects.

Recent experiments have revealed multiple borophene phases of distinct lattice structures, suggesting that the unit cells of and boron sheets, namely and chains, serve as building blocks to assemble into novel borophene phases. Motivated by these experiments, we present a theoretical study of electron transport along two-terminal quasiperiodic borophene nanoribbons (BNRs), with the arrangement of the and chains following the generalized Fibonacci sequence. Our results indicate that the energy spectrum of these quasiperiodic BNRs is multifractal and characterized by numerous transmission peaks.