Exploring Object Relation in Mean Teacher for Cross-Domain Detection

Rendering synthetic data (e.g., 3D CAD-rendered images) to generate annotations for learning deep models in vision tasks has attracted increasing attention in recent years. However, simply applying the models learnt on synthetic images may lead to high generalization error on real images due to domain shift. To address this issue, recent progress in cross-domain recognition has featured the Mean Teacher, which directly simulates unsupervised domain adaptation as semi-supervised learning. The domain gap is thus naturally bridged with consistency regularization in a teacher-student scheme. In this work, we advance this Mean Teacher paradigm to be applicable for cross-domain detection. Specifically, we present Mean Teacher with Object Relations (MTOR) that novelly remolds Mean Teacher under the backbone of Faster R-CNN by integrating the object relations into the measure of consistency cost between teacher and student modules. Technically, MTOR firstly learns relational graphs that capture similarities between pairs of regions for teacher and student respectively. The whole architecture is then optimized with three consistency regularizations: 1) region-level consistency to align the region-level predictions between teacher and student, 2) inter-graph consistency for matching the graph structures between teacher and student, and 3) intra-graph consistency to enhance the similarity between regions of same class within the graph of student. Extensive experiments are conducted on the transfers across Cityscapes, Foggy Cityscapes, and SIM10k, and superior results are reported when comparing to state-of-the-art approaches. More remarkably, we obtain a new record of single model: 22.8% of mAP on Syn2Real detection dataset.Comment: CVPR 2019; The codes and model of our MTOR are publicly available at: https://github.com/caiqi/mean-teacher-cross-domain-detectio

The Design Concept and Realization of University Library’s Online Lecture System

The traditional library lectures are based on the physical space environment, which is problematic in terms of user needs analysis, time selection, and resource utilization, so that the value of the library unexploited.University library’s online lecture system adopts the three-tier architecture design pattern, which based on ASP.NET as the development platform and SQL Server as the back-end database, designing the system to solve the problems in the traditional library service.The design and implementation of the University library’s online lecture system broke the traditional library lecture mode, and further optimized the library service concept, improve the quality of service to meet the diverse needs of the user groups. Integrating online test, interactive question and answer, feedback mechanism to the system, the system has a good user experience, visual way to show the audience’s learning situation and other information, optimize the content and quality of services to make comments and suggestions

Dynamic Property and Magnetic Nonpotentiality of Two Types of Confined Solar Flares

We analyze 152 large confined flares (GOES class $\geq$M1.0 and $\leq$$45^{\circ}$ from disk center) during 2010$-$2019, and classify them into two types according to the criterion taken from the work of Li et al. (2019). "Type I" flares are characterized by slipping motions of flare loops and ribbons and a stable filament underlying the flare loops. "Type II" flares are associated with the failed eruptions of the filaments, which can be explained by the classical 2D flare model. A total of 59 flares are "Type I" flares (about 40\%) and 93 events are "Type II" flares (about 60\%). There are significant differences in distributions of the total unsigned magnetic flux ($\Phi$$_\mathrm{AR}$) of active regions (ARs) producing the two types of confined flares, with "Type I" confined flares from ARs with a larger $\Phi$$_{AR}$ than "Type II". We calculate the mean shear angle $\Psi$$_\mathrm{HFED}$ within the core of an AR prior to the flare onset, and find that it is slightly smaller for "Type I" flares than that for "Type II" events. The relative non-potentiality parameter $\Psi$$_\mathrm{HFED}$/$\Phi$$_\mathrm{AR}$ has the best performance in distinguishing the two types of flares. About 73\% of "Type I" confined flares have $\Psi$$_\mathrm{HFED}$/$\Phi$$_\mathrm{AR}$$<$1.0$\times$$10^{-21}$ degree Mx$^{-1}$, and about 66\% of "Type II" confined events have $\Psi$$_\mathrm{HFED}$/$\Phi$$_\mathrm{AR}$$\geq$1.0$\times$$10^{-21}$ degree Mx$^{-1}$. We suggest that "Type I" confined flares cannot be explained by the standard flare model in 2D/3D, and the occurrence of multiple slipping magnetic reconnections within the complex magnetic systems probably leads to the observed flare.Comment: 11 pages, 8 figure

Indonesian Muslim Women and the Gender Equality Movement

Throughout the history of Indonesia, the concepts of gender and power-relations between men and women have been linked to a shifting and fluctuating idea of what constitutes good women, good men, and good gender relationships within the context of Indonesia and Islam. To analyse these changing attitudes to women\u27s issues in Indonesia, we need to pay attention to several points: the character of the women\u27s organizations, whether fully independent, semi autonomous, or subsidiaries of existing male organizations; the important issues rising within the movements, as well as the strategies to deal with them; and lastly the influential factor of government intervention in the women\u27s movement. This paper tries to explore the Muslim women\u27s movement and its strategy to accommodate or resist from the domination of Islam in terms of the nation state, the constitution and the dominant cultural norms in Indonesia

Analysis of Ophthalmic Examination Results of 7364 Cases in Kunming Regional Health Management Center

Objective To understand the distribution of eye diseases in the tested population, and to provide a reference basis for the prevention, diagnosis and treatment of eye diseases. Methods A total of 7, 364 patients in the Health Management Center from June 2022 to September 2022 underwent eye examination, and the statistical analysis of their eye examination results was conducted by retrospective analysis. Results Of the 7, 364 patients, 6, 202 cases(84. 22%) had a history of eye disease or eye surgery, and the top five eye diseases were refractive error(75. 35%), cataract(18. 06%), pterygium(4. 09%), pinguecula(3. 57%), fundus tigre(2. 70%). Conclusion In the tested population, the prevalence of refractive error was the highest, followed by cataract, pterygium and so on in men Blebral spot, ptosis. More cataracts and fundus arteriosclerosis, and more women suffer from corneal diseases and trichiasis. There is no obvious difference between men and women, and middle-aged and elderly people have a higher probability of cataract and fundus diseases