Semantic Discriminant mapping for classification and browsing of remote sensing textures and objects

We present a new approach based on Discriminant Analysis to map a high dimensional image feature space onto a subspace which has the following advantages: 1. each dimension corresponds to a semantic likelihood, 2. an efficient and simple multiclass classifier is proposed and 3. it is low dimensional. This mapping is learnt from a given set of labeled images with a class groundtruth. In the new space a classifier is naturally derived which performs as well as a linear SVM. We will show that projecting images in this new space provides a database browsing tool which is meaningful to the user. Results are presented on a remote sensing database with eight classes, made available online. The output semantic space is a low dimensional feature space which opens perspectives for other recognition tasks. © 2005 IEEE.

Sequencing, annotation and comparative analysis of nine BACs of giant panda (Ailuropoda melanoleuca)

A 10-fold BAC library for giant panda was constructed and nine BACs were selected to generate finish sequences. These BACs could be used as a validation resource for the de novo assembly accuracy of the whole genome shotgun sequencing reads of giant panda newly generated by the Illumina GA sequencing technology. Complete sanger sequencing, assembly, annotation and comparative analysis were carried out on the selected BACs of a joint length 878 kb. Homologue search and de novo prediction methods were used to annotate genes and repeats. Twelve protein coding genes were predicted, seven of which could be functionally annotated. The seven genes have an average gene size of about 41 kb, an average coding size of about 1.2 kb and an average exon number of 6 per gene. Besides, seven tRNA genes were found. About 27 percent of the BAC sequence is composed of repeats. A phylogenetic tree was constructed using neighbor-join algorithm across five species, including giant panda, human, dog, cat and mouse, which reconfirms dog as the most related species to giant panda. Our results provide detailed sequence and structure information for new genes and repeats of giant panda, which will be helpful for further studies on the giant panda.

Initializing Vision Based Trackers Using Semantic Texton Forests

Vision based tracking can provide the spatial location of project related entities such as equipment, workers, and materials in a large-scale congested construction site. It tracks entities in a video stream by inferring their motion. To initiate the process, it is required to determine the pixel areas of the entities to be tracked in the following consecutive video frames. For the purpose of fully automating the process, this paper presents an automated way of initializing trackers using Semantic Texton Forests (STFs) method. STFs method performs simultaneously the segmentation of the image and the classification of the segments based on the low-level semantic information and the context information. In this paper, STFs method is tested in the case of wheel loaders recognition. In the experiments, wheel loaders are further divided into several parts such as wheels and body parts to help learn the context information. The results show 79% accuracy of recognizing the pixel areas of the wheel loader. These results signify that STFs method has the potential to automate the initialization process of vision based tracking.

Learning based automatic face annotation for arbitrary poses and expressions from frontal images only

Statistical approaches for building non-rigid deformable models, such as the Active Appearance Model (AAM), have enjoyed great popularity in recent years, but typically require tedious manual annotation of training images. In this paper, a learning based approach for the automatic annotation of visually deformable objects from a single annotated frontal image is presented and demonstrated on the example of automatically annotating face images that can be used for building AAMs for fitting and tracking. This approach employs the idea of initially learning the correspondences between landmarks in a frontal image and a set of training images with a face in arbitrary poses. Using this learner, virtual images of unseen faces at any arbitrary pose for which the learner was trained can be reconstructed by predicting the new landmark locations and warping the texture from the frontal image. View-based AAMs are then built from the virtual images and used for automatically annotating unseen images, including images of different facial expressions, at any random pose within the maximum range spanned by the virtually reconstructed images. The approach is experimentally validated by automatically annotating face images from three different databases. © 2009 IEEE.

Semantic transform: Weakly supervised semantic inference for relating visual attributes

Relative (comparative) attributes are promising for thematic ranking of visual entities, which also aids in recognition tasks. However, attribute rank learning often requires a substantial amount of relational supervision, which is highly tedious, and apparently impractical for real-world applications. In this paper, we introduce the Semantic Transform, which under minimal supervision, adaptively finds a semantic feature space along with a class ordering that is related in the best possible way. Such a semantic space is found for every attribute category. To relate the classes under weak supervision, the class ordering needs to be refined according to a cost function in an iterative procedure. This problem is ideally NP-hard, and we thus propose a constrained search tree formulation for the same. Driven by the adaptive semantic feature space representation, our model achieves the best results to date for all of the tasks of relative, absolute and zero-shot classification on two popular datasets. © 2013 IEEE.

semantic oriented ontology cohesion metrics for ontology-based systems

Ontologies play a core role to provide shared knowledge models to semantic-driven applications targeted by Semantic Web. Ontology metrics become an important area because they can help ontology engineers to assess ontology and better control project management and development of ontology based systems, and therefore reduce the risk of project failures. In this paper, we propose a set of ontology cohesion metrics which focuses on measuring (possibly inconsistent) ontologies in the context of dynamic and changing Web. They are: Number of Ontology Partitions (NOP), Number of Minimally Inconsistent Subsets (NMIS) and Average Value of Axiom Inconsistencies (AVAI). These ontology metrics are used to measure ontological semantics rather than ontological structure. They are theoretically validated for ensuring their theoretical soundness, and further empirically validated by a standard test set of debugging ontologies. The related algorithms to compute these ontology metrics also are discussed. These metrics proposed in this paper can be used as a very useful complementarity of existing ontology cohesion metrics.

Expressed sequence tags from the zhikong scallop (Chlamys farreri): Discovery and annotation of host-defense genes

A high-quality cDNA library was constructed from whole body tissues of the zhikong scallop, Chlamys farreri, challenged by Listonella anguillarum. A total of 5720 clones were sequenced, yielding 5123 expressed sequence tags (ESTs). Among the 3326 unique genes identified, 2289 (69%) genes had no significant (E-value < 1e-5) matches to known sequences in public databases and 194 (6%) matched proteins of unknown functions. The remaining 843 (25%) genes that exhibited homology with genes of known functions, showed broad involvement in metabolic processes (31%), cell structure and motility (20%), gene and protein expression (12%), cell signaling and cell communication (8%), cell division (4%), and notably, 25% of those genes were related to immune function. They included stress response genes, complement-like genes, proteinase and proteinase inhibitors, immune recognition receptors and immune effectors. The EST collection obtained in this study provides a useful resource for gene discovery and especially for the identification of host-defense genes and systems in scallops and other molluscs. (C) 2009 Elsevier Ltd. All rights reserved.

Discovery of immune related factors in Fenneropenaeus chinensis by annotation of ESTs

A total of 10446 expressed sequence tags (ESTs) are obtained by a large-scale sequencing of a cDNA library from cephalothorax of adult Fenneropenaeus chinensis. An EST analysis platform was built up based on local computers and bioinformatic techniques were used to annotate these ESTs in order to promptly find possible functional genes, especially for immune related factors. About 4% of the ESTs show similarity to the coding sequences of such factors, including lectin, serine protease, serpin, lysozyme, etc. These ESTs provide a partial profile of the immune system in F. chinensis and useful information for further study on these genes.

Discovery of genes involved in defense/immunity functions in a haemocytes cDNA library from Fenneropenaeus chinensis by ESTs annotation

Crustacean haemocytes play important roles in the host immune response including recognition, phagocytosis, melanization, cytotoxicity and inter-cellular signal communication. Expressed sequence tags (ESTs) analysis is proved to be an efficient approach not only for gene discovery, but also for gene expression profiles performance. In order to further understand the innate immune system and defense mechanisms of Chinese shrimp at molecular level, complementary DNA library is constructed from the haemocyte tissue of Fenneropenaeus chinensis. A total of 2371 cDNA clones are successfully sequenced and the average sequence length is 460 bp. About 50% are identified as orthologs of known genes from other organisms by BLASTx and BLASTn program. By sequences comparability and analysis, 34 important genes including 177 ESTs are identified that may be involved in defense or immune functions in shrimp based on the known knowledge. These genes are categorized into five categories according to their putative functions in shrimp immune system: 13 genes are different types of antimicrobial peptides (AMP, penaeidin, antilipopolysaccharide factor, etc.), and their proportion is about 3 8%; 11 genes belong to prophenoloxidase system (prophenoloxidase, serine proteinase, serine proteinase inhibitor, etc.), and their proportion is about 32%; five genes have high homology with clotting protein (lectin, transglutaminase, etc), and their proportion is about 15%; three genes may be involved in inter-cell signal communication (peroxinectin, integrin), and their proportion is about 9%; two genes have been identified to be chaperone proteins (Hsc70, thioredoxin peroxidase), and their proportion is about 6%. These EST sequences enrich our understanding of the immune genes of F chinensis and will help farther experimental research into immune factors and improve our knowledge of the immune mechanisms of shrimp. (c) 2007 Elsevier B.V. All rights reserved.