Semi-automatic Annotation Method of Infrared Sequence Images Based on Image Significance

Author(s):  
Chuang Liu ◽  
Pan Huang ◽  
Xiaogang Yang ◽  
Ruitao Lu
2019 ◽  
Vol 8 (2S8) ◽  
pp. 1346-1350

The research literature on sentiment analysis methodologies has exponentially grown in recent years. In any research area, where new concepts and techniques are constantly introduced, it is, therefore, of interest to analyze the latest trends in this literature. In particular, we have chosen to primarily focus on the literature of the last five years, on annotation methodologies, including frequently used datasets and from which they were obtained. Based on the survey, it appears that researchers do more manual annotation in the formation of sentiment corpus. As for the dataset, there are still many uses of English language taken from social media such as Twitter. In this area of research, there are still many that need to be explored, such as the use of semi-automatic annotation method that is still very rarely used by researchers. Also, less popular languages, such as Malay, Korean, Japanese, and so on, still require corpus for sentiment analysis research.


2018 ◽  
Vol 14 (4) ◽  
pp. 1-19 ◽  
Author(s):  
Na Deng ◽  
Chunzhi Wang ◽  
Mingwu Zhang ◽  
Zhiwei Ye ◽  
Liang Xiao ◽  
...  

In the era of big data, the latest and most advanced technologies are usually revealed to the world in the form of patents. Patents include abundant technical, economic and legal information. A deep analysis and mining of patents can provide important support for enterprises. Patent effect annotation is an important step in patent analysis and mining, and the extraction of patent effect clue words can greatly improve the accuracy and recall rate of annotation. This article summarizes the classification and characteristics of effect clue words, and proposes a co-training-based method of extracting effect clue words from Chinese patents suitable for various fields. Through a strategy called self-filtering, this method can gradually enrich effect clue words thesaurus by iterations, not relying on any other third-party filters. The experiments give the detailed steps, comparisons and boosting of the method.


2021 ◽  
Vol 187 ◽  
pp. 432-439
Author(s):  
Guibin Wu ◽  
Junjie Zhou ◽  
Jingshu Yang ◽  
Xiaobing Lv ◽  
Yongping Xiong

Author(s):  
Guibin Wu ◽  
Junjie Zhou ◽  
Yongping Xiong ◽  
Chaoyi Zhou ◽  
Chong Li

AbstractUsing deep learning networks to recognize the table attracts lots of attention. However, due to the lack of high-quality table datasets, the performance of using deep learning networks is limited. Therefore, TableRobot has been proposed, an automatic annotation method for heterogeneous tables. To be more specific, the annotations of table consist of the coordinates of the item block and the mapping relationship between item blocks and table cells. In order to transform the task, we successfully design an algorithm based on the greedy approach to find the optimum solution. To evaluate the performance of TableRobot, we check the annotation data of 3000 tables collected from the LaTex documents in arXiv.com, and the result shows that TableRobot can generate table annotation datasets with the accuracy of 93.2%. Besides, the table annotation data is feed into GraphTSR which is a state-of-the-art table recognition graph neural network, and the F1 value of the network has increased by nearly 10% compared with before.


2019 ◽  
Author(s):  
Yu Toyoshima ◽  
Stephen Wu ◽  
Manami Kanamori ◽  
Hirofumi Sato ◽  
Moon Sun Jang ◽  
...  

AbstractAnnotation of cell identity is an essential process in neuroscience that allows for comparing neural activities across different animals. In C. elegans, although unique identities have been assigned to all neurons, the number of annotatable neurons in an intact animal is limited in practice and comprehensive methods for cell annotation are required. Here we propose an efficient annotation method that can be integrated with the whole-brain imaging technique. We systematically identified neurons in the head region of 311 adult worms using 35 cell-specific promoters and created a dataset of the expression patterns and the positions of the neurons. The large positional variations illustrated the difficulty of the annotation task. We investigated multiple combinations of cell-specific promoters to tackle this problem. We also developed an automatic annotation method with human interaction functionality that facilitates annotation for whole-brain imaging.


2022 ◽  
Vol 40 (1) ◽  
pp. 71-82
Author(s):  
Shogo Okano ◽  
Tatsuhito Makino ◽  
Kosei Demura

Sign in / Sign up

Export Citation Format

Share Document