Existing Siamese trackers usually do not update templates or adopt single‐updating strategies. However, historical information cannot be effectively utilized when using these strategies, and model drift from complex tracking challenges cannot be addressed. To address this issue, a novel tracking framework that learns the model update with local trusted templates is proposed in this paper. The authors propose a complementary confidence evaluation method to select local trusted templates in a sliding window. This provides high‐confidence historical information. The authors also propose a method including linear learning and deep learning to learn to model updates. Different from traditional update strategies, the authors’ method combines non‐linear and linear updates to obtain reliable templates with the most abundant historical information, which solves the complex tracking challenges to a certain extent. Finally, the adaptive fusion response maps of the two strategies determine the final tracking based on the confidence evaluation. Experimental results on NFS, UAVDT, UAV123, UAV20L and VOT2016 show that our method performs favourably when compared with current state‐of‐the‐art methods.

Background To explore the clinical significance of digital tomographic fusion imaging in the diagnosis of avascular disease of the femoral head in adults. Methods Eighty-two adult patients with avascular necrosis of the femoral head confirmed by MRI in the department of orthopedics of our hospital were studied retrospectively. The related signs of adult avascular necrosis of the femoral head were diagnosed by digital tomographic fusion imaging, and the detection rates of digital X-ray (DR) and digital tomosynthesis (DTS) were compared to clarify the clinical value of digital tomographic fusion imaging in the diagnosis of adult avascular necrosis of the femoral head. Results DTS detected DR and 78 cases identified 55 cases. Taking the results of CT/MRI as the gold standard, the sensitivity, specificity, positive predictive value, and negative predictive value of DR and DTS in the diagnosis of ANFH were calculated. There was a significant difference in the detection rate between the two methods (P < 0.05). Conclusion The digital tomographic fusion imaging technique has the advantages of high detection rate and excellent image quality, is economical, and is worth popularizing. For those with negative X-rays, DTS diagnosis and CT or/and MRI can avoid unnecessary CT and MRI examinations, which is helpful to reduce the waste of medical resources.

No abstract

No abstract