Publications by authors named "Shixue Zhang"

Article Synopsis
  • This study introduces a new method for enhancing the autonomous stable tracking capabilities of electro-optical theodolites used in closed-loop systems.
  • The approach utilizes a multi-sensor adaptive weighted fusion algorithm, which includes a refined error estimation formula to ensure accurate data processing and sensor state assignments.
  • Experimental results show that the algorithm can quickly switch to alternative sensors during interference or failures, maintaining robustness and stability in data generation across different measurement conditions.
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Scene text spotting is a challenging task, especially for inverse-like scene text, which has complex layouts, e.g., mirrored, symmetrical, or retro-flexed.

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Fluorinated carbon (CFx) has ultrahigh theoretical energy density among cathode materials for lithium primary batteries. CFx, as an active material in the cathode, plays a decisive role in performance. However, the performance of commercialized fluorinated graphite (FG) does not meet this continuously increasing performance demand.

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A time-resolved electron paramagnetic resonance (TREPR) method with 40 ns time resolution and a high sensitivity suitable for the detection of short-lived radicals under thermal equilibrium is developed. The key is the introduction of a new detection technique named ultrawide single sideband phase sensitive detection (U-PSD) to the conventional continuous-wave EPR, which remarkably enhanced the sensitivity for the detection of broadband transient signals compared with the direct detection protocol. By repeatedly triggering a transient kinetic event f(t) (e.

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Arbitrary shape text detection is a challenging task due to the significantly varied sizes and aspect ratios, arbitrary orientations or shapes, inaccurate annotations, etc. Due to the scalability of pixel-level prediction, segmentation-based methods can adapt to various shape texts and hence attracted considerable attention recently. However, accurate pixel-level annotations of texts are formidable, and the existing datasets for scene text detection only provide coarse-grained boundary annotations.

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Segmentation-based methods have achieved great success for arbitrary shape text detection. However, separating neighboring text instances is still one of the most challenging problems due to the complexity of texts in scene images. In this article, we propose an innovative kernel proposal network (dubbed KPN) for arbitrary shape text detection.

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Background: The classic duodenal switch (DS) represents a minority of bariatric procedures due to its high complexity and potential for complications.

Methods: A retrospective chart review was conducted on 100 laparoscopic DS cases from 2014 to 2018 at an accredited program in a rural community hospital and compared to 100 laparoscopic Roux-en-Y gastric bypasses (RYGB). Primary outcomes were 30-day morbidity and mortality.

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We present an improved method to generate Airy beams utilizing a liquid crystal on silicon (LCoS) device. In this method, the phase and amplitude information of a modified Fourier spectrum of an Airy beam together with a Fresnel holographic lens is encoded onto the LCoS using the phase-only filter technique; thus, a desired Airy beam is formed in the focal plane of the Fresnel holographic lens. In this paper, the principle of the proposed method is described in detail, and both the excellent numerical simulations and experimental results for verifying this method are demonstrated.

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