Annotation

About: Annotation is a research topic. Over the lifetime, 6719 publications have been published within this topic receiving 203463 citations. The topic is also known as: note & markup.

Automatic recognition and annotation of gene expression patterns of fly embryos

Abstract: Motivation: Gene expression patterns obtained by in situ mRNA hybridization provide important information about different genes during Drosophila embryogenesis. So far, annotations of these images are done by manually assigning a subset of anatomy ontology terms to an image. This time-consuming process depends heavily on the consistency of experts. Results: We develop a system to automatically annotate a fruitfly's embryonic tissue in which a gene has expression. We formulate the task as an image pattern recognition problem. For a new fly embryo image, our system answers two questions: (1) Which stage range does an image belong to? (2) Which annotations should be assigned to an image? We propose to identify the wavelet embryo features by multi-resolution 2D wavelet discrete transform, followed by min-redundancy max-relevance feature selection, which yields optimal distinguishing features for an annotation. We then construct a series of parallel bi-class predictors to solve the multi-objective annotation problem since each image may correspond to multiple annotations. Supplementary information: The complete annotation prediction results are available at: http://www.cs.niu.edu/~jzhou/papers/fruitfly and http://research.janelia.org/peng/proj/fly_embryo_annotation/. The datasets used in experiments will be available upon request to the correspondence author. Contact:jzhou@cs.niu.edu and pengh@janelia.hhmi.org

Learning Visual Contexts for Image Annotation From Flickr Groups

Abstract: We present an extension of automatic image annotation that takes the context of a picture into account. Our core assumption is that users do not only provide individual images to be tagged, but group their pictures into batches (e.g., all snapshots taken over the same holiday trip), whereas the images within a batch are likely to have a common style. These batches are matched with categories learned from Flickr groups, and an accurate context-specific annotation is performed.

Semantic annotation and retrieval of video events using multimedia ontologies

Abstract: Effective usage of multimedia digital libraries has to deal with the problem of building efficient content annotation and retrieval tools. In this paper multimedia ontologies, that include both linguistic and dynamic visual ontologies, are presented and their implementation for soccer video domain is shown. The structure of the proposed ontology itself, together with reasoning, can be used to perform higher-level annotation of the clips, to generate complex queries that comprise actions and their temporal evolutions and relations and to create extended text commentaries of video sequences.

Proposal for an Extension of Traditional Named Entities: From Guidelines to Evaluation, an Overview

Abstract: Within the framework of the construction of a fact database, we defined guidelines to extract named entities, using a taxonomy based on an extension of the usual named entities definition. We thus defined new types of entities with broader coverage including substantive-based expressions. These extended named entities are hierarchical (with types and components) and compositional (with recursive type inclusion and metonymy annotation). Human annotators used these guidelines to annotate a 1.3M word broadcast news corpus in French. This article presents the definition and novelty of extended named entity annotation guidelines, the human annotation of a global corpus and of a mini reference corpus, and the evaluation of annotations through the computation of inter-annotator agreements. Finally, we discuss our approach and the computed results, and outline further work.

CAT: the CELCT Annotation Tool

Abstract: This paper presents CAT - CELCT Annotation Tool, a new general-purpose web-based tool for text annotation developed by CELCT (Center for the Evaluation of Language and Communication Technologies). The aim of CAT is to make text annotation an intuitive, easy and fast process. In particular, CAT was created to support human annotators in performing linguistic and semantic text annotation and was designed to improve productivity and reduce time spent on this task. Manual text annotation is, in fact, a time-consuming activity, and conflicts may arise with the strict deadlines annotation projects are frequently subject to. Thanks to its adaptability and user-friendly interface, CAT can positively contribute to improve time management in annotation project. Further, the tool has a number of features which make it an easy-to-use tool for many types of annotations. Even if the first prototype of CAT has been used to perform temporal and event annotation following the It-TimeML specifications, the tool is general enough to be used for annotating a broad range of linguistic and semantic phenomena. CAT is freely available for research purposes.