We address the problem of detecting tree rings in microscopy images of shrub
cross sections. This can be regarded as a special case of the instance
segmentation task with several unique challenges such as the concentric
circular ring shape of the objects and high precision requirements that result
in inadequate performance of existing methods. We propose a new iterative
method which we term Iterative Next Boundary Detection (INBD). It intuitively
models the natural growth direction, starting from the center of the shrub
cross section and detecting the next ring boundary in each iteration step. In
our experiments, INBD shows superior performance to generic instance
segmentation methods and is the only one with a built-in notion of
chronological order. Our dataset and source code are available at
this http URL

本文提出了一种新的迭代法，即迭代下一边界检测算法（INBD），它通过模拟自然生长方向，从植物截面的中心开始，在每个迭代步骤中检测下一个环形边界，解决了检测显微镜图像中的树轮等多个环状物体的问题，并且优于常规实例分割方法，是唯一具有内置时间顺序概念的方法。

针对灌木截面显微镜图像中树木年轮的实例分割的迭代式下一个边界检测

Iterative Next Boundary Detection for Instance Segmentation of Tree  Rings in Microscopy Images of Shrub Cross Sections

The problem of organizing information for multidocument summarization so that
the generated summary is coherent has received relatively little attention.
While sentence ordering for single document summarization can be determined
from the ordering of sentences in the input article, this is not the case for
multidocument summarization where summary sentences may be drawn from different
input articles. In this paper, we propose a methodology for studying the
properties of ordering information in the news genre and describe experiments
done on a corpus of multiple acceptable orderings we developed for the task.
Based on these experiments, we implemented a strategy for ordering information
that combines constraints from chronological order of events and topical
relatedness. Evaluation of our augmented algorithm shows a significant
improvement of the ordering over two baseline strategies.

本研究旨在提出一种新闻类多文档摘要中信息排序的方法，该方法综合考虑事件的时间先后和主题相关性约束，经实验证实了该方法相对于两种基准方法有显著的排序改进。