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This invention discloses a feature denoising distillation method guided by Logit information, belonging to the field of model compression technology. The method includes: first, encoding the discriminative direction of the teacher classifier using a Logit discriminative encoder to ensure feature alignment along the semantic direction; then, constructing a feature denoising mask to emphasize the teacher's target attention region while suppressing redundant background responses, thereby achieving spatial-level denoising in the feature space. Finally, a feature denoising distillation framework guided by Logit information is designed to achieve model compression. This invention provides explicit semantic direction guidance through a Logit discriminative encoder, suppresses background and noise activation through a feature denoising mask, and integrates both into the intermediate feature distillation process between the teacher and student models. It systematically solves the problems of lack of Logit semantic guidance, severe background noise interference, and insufficient focus of the distillation target in existing technologies, achieving high-precision and highly compatible model compression and knowledge transfer.

This disclosure provides a method and system for enhancing low-exposure images based on embedded McLaurin and convolution, relating to the field of image processing technology. The method involves acquiring a low-exposure image to be enhanced, processing and decomposing the low-exposure image, inputting the low-exposure image into a backbone network to extract multi-scale features, introducing a dynamic adjustment factor into the backbone network, using the dynamic adjustment factor to learn a convolution weight calibration map, calibrating the convolution weights of the backbone network with the learned weight calibration map, performing convolution operations on the features using the calibrated convolution kernels to obtain the luminance component of the low-exposure image, and outputting a long-exposure enhanced image that varies with the dynamic adjustment factor using the luminance component.

This invention discloses a AIPL1 A gene mutation-related congenital amaurosis animal model, its construction method, and its application. The method includes: S1, constructing a humanized... AIPL1 S2, a homologous recombination vector with a point mutation of c.421 C>T (p.Q141X) knocked in; S3, Cas9 mRNA, gRNA1, gRNA2 and the homologous recombination vector are injected into animal zygotes to perform homologous recombination, resulting in transfected zygotes; S4, the transfected zygotes are transplanted into the uterus of pseudopregnant animals to reproduce offspring, and offspring are selected from the offspring. AIPL1 Homozygous animals with the c.421 C>T (p.Q141X) point mutation were obtained, thus yielding the aforementioned... AIPL1 A gene mutation-related congenital amaurosis animal model. The animal model of this invention exhibits the clinical phenotype of Leber congenital amaurosis type 4 (LCA4) from 12 days after birth; while heterozygous mice do not show a significant phenotype, consistent with... AIPL1 The clinical phenotype and inheritance pattern of LCA caused by the c.421 C>T (p.Q141X) gene mutation demonstrate the effectiveness and reliability of the animal model of this invention, providing a basis for understanding the genetic model of LCA. AIPL1 Animal models provide a reliable basis for studying the disease mechanisms and drug screening of mutation-related LCA.

This invention discloses a multipath ghosting elimination method for indoor target localization, comprising the following steps: Step 1, initial target localization; Step 2, mirror target position calculation; Step 3, theoretical position calculation of single-path first reflection + single-path LOS path; Step 4, theoretical position calculation of single-path LOS path + single-path first reflection; Step 5, multipath position matching and elimination. The method disclosed in this invention utilizes millimeter-wave radar to perform multipath elimination and subsequent localization of targets in an indoor multipath environment. Based on the propagation phenomena of electromagnetic waves, the main propagation paths of electromagnetic waves in indoor multipath scenarios are analyzed, and the theoretical positions of combined paths and two-way first reflection paths are calculated. This removes the multipath positioning points from the final target calculation results, obtaining the true target positioning trace. Experimental results demonstrate the accuracy of the method in locating true targets and the effectiveness of multipath elimination.