Deep learning has been widely used in various sensor detection fields to realize intelligent detection tasks. However, there are always restrictions on how these functions can be integrated into embedded devices to complete mobile and convenient sensing detection tasks. Therefore, the MobileNet_SSD, A lightweight model after simplification and optimization, is used in this paper to design a portable visual sensor system for the detection of spray droplet deposition in drone applications. The sensing system includes a droplet deposition image loop acquisition device and a supporting host computer interactive platform. It introduces the Sarsa algorithm to establish an adaptive model of light intensity to enhance the robustness and combines Deep Neural Networks and image processing technology to achieve rapid loop detection of droplet deposition parameters on the mobile terminal. Experimental results indicate that the proposed sensor can adapt to light changes in complex environments, and accurately measure the deposition parameters of different droplet density images. Furthermore, it is of great significance to detect the quality of drone sprays, master the rules of droplet deposition, and understand the effects of pesticide spraying.

CD59 is a GPI-linked membrane protein that inhibits formation of the membrane attack complex of complement. We reported recently that mice have two CD59 genes (termed mCd59a and mCd59b), and that the targeted deletion of mCd59b (mCd59b^−/−) results in spontaneous hemolytic anemia and progressive loss of male fertility. Further studies of the reproductive abnormalities in mCd59b^−/− mice reported in this study revealed the presence of abnormal multinucleated cells and increased apoptotic cells within the walls of the seminiferous tubules, and a decrease in the number, motility, and viability of sperm associated with a significant increase in abnormal sperm morphologies. Both the capacitation-associated tyrosine phosphorylation and the ionophore-induced acrosome reaction as well as luteinizing hormone, follicle-stimulating hormone, and testosterone serum levels were similar in mCd59b^−/− and mCd59b^+/+. Surprisingly, the functional deficiency of the complement protein C3 did not rescue the abnormal reproductive phenotype of mCd59b^−/−, although it was efficient in rescuing their hemolytic anemia. These results indicate that the male reproductive abnormalities in mCd59b^−/− are complement-independent, and that mCd59 may have a novel function in spermatogenesis that is most likely unrelated to its function as an inhibitor of membrane attack complex formation.

Automatic fine registration of multisensor images plays an essential role in many remote sensing applications. However, it is always a challenging task due to significant radiometric and textural differences. In this paper, an enhanced subpixel phase correlation method is proposed, which embeds phase congruency-based structural representation, L₁-norm-based rank-one matrix approximation with adaptive masking, and stable robust model fitting into the conventional calculation framework in the frequency domain. The aim is to improve the accuracy and robustness of subpixel translation estimation in practical cases. In addition, template matching using the enhanced subpixel phase correlation is integrated to realize reliable fine registration, which is able to extract a sufficient number of well-distributed and high-accuracy tie points and reduce the local misalignment for coarsely coregistered multisensor remote sensing images. Experiments undertaken with images from different satellites and sensors were carried out in two parts: tie point matching and fine registration. The results of qualitative analysis and quantitative comparison with the state-of-the-art area-based and feature-based matching methods demonstrate the effectiveness and reliability of the proposed method for multisensor matching and registration.

Combined geometric positioning using images with different resolutions and imaging sensors is being increasingly widely utilized in practical engineering applications. In this work, we attempt to perform the combined geometric positioning and performance analysis of multi-resolution optical images from satellite and aerial platforms based on weighted rational function model (RFM) bundle adjustment without using ground control points (GCPs). Firstly, we introduced an integrated image matching method combining least squares and phase correlation. Next, for bundle adjustment, a combined model of the geometric positioning based on weighted RFM bundle adjustment was derived, and a method for weight determination was given to make the weights of all image points variable. Finally, we conducted experiments using a case study in Shanghai with ZiYuan-3 (ZY-3) satellite imagery, GeoEye-1 satellite imagery, and Digital Mapping Camera (DMC) aerial imagery to validate the effectiveness of the proposed weighted method, and to investigate the positioning accuracy by using different combination scenarios of multi-resolution heterogeneous images. The experimental results indicate that the proposed weighted method is effective, and the positioning accuracy of different combination scenarios can give a good reference for the combined geometric positioning of multi-stereo heterogeneous images in future practical engineering applications.

The excellent performance of geometric positioning of a newly launched satellite will greatly broaden its application field. Launched on January 15, 2020, the Hongqi-1-H9 wide-range satellite is the largest sub-meter-level satellite worldwide and the first ton-level commercial remote sensing satellite in China, with a resolution of less than 1 m and a swath width of 136 km. This study was aimed at assessing the geometric positioning accuracy of this newly launched satellite considering three aspects, namely, the circle error accuracy, rational polynomial coefficient-based direct geometric positioning accuracy and ground control point-based absolute positioning accuracy under urban, plain, and mountainous areas, with different topographies. The results of the conducted experimental investigation indicated that the Hongqi-1-H9 satellite could exhibit a high positioning accuracy in planar and vertical directions for different terrains. In particular, for our experimental areas with a low topography and few surface structures, the geometric positioning accuracy of the Hongqi-1-H9 satellite imagery was less than 4m and 2 m in the planimetry and elevation directions, respectively. These characteristics can promote the application of the Hongqi-1-H9 satellite images in agricultural surveys, target detection, and land surveys, among other domains.