Sentence examples for retrieval datasets from inspiring English sources

Furthermore, the orientation attributes of the local features are provided in most popular large-scale image retrieval datasets, such as Holidays [19] and Oxfor5K [17].

We extend our recent benchmark for testing canonical form algorithms. Our new benchmark is used to evaluate a greater number of state-of-the-art canonical forms, on five recent non-rigid retrieval datasets, within two different retrieval frameworks.

In image retrieval, various datasets are used for several purposes; these includes Corel dataset, MIT dataset and Brodtz texture dataset etc.

We then compared the performance of our algorithm for motif retrieval on Dataset-2 by the 'best hit' method to that of STAMP [8] and a Bayesian learning algorithm [23] as both algorithms have been applied by their authors to this dataset for the same purpose.

Table 3 Time needed for phase retrieval [23] for different datasets Dataset Phase retrieval time (s) Single projection Full dataset Ultrafast 0.3 1.4 Fast 0.6 6.6 Standard 6 85.5 Highres 6 106.6.

Table 3 summarizes the time required for phase retrieval for the datasets listed in Table 1.

Apart from text search, several browsing options facilitate the retrieval of important datasets, such as entries for a particular organism or hormone name or specific domain or domain combinations etc.

However, annotation of experimental data in GEO still makes little use of controlled vocabularies (e.g ontologies), which is necessary for automated retrieval of relevant datasets for specific large-scale studies.

To avoid this overhead, the dataset RDF/XML serialization was re-implemented to use the Streaming API for XML (StAX) [37], resulting in reduced response time of dataset retrieval (2-10 timprovementement, depending on the size of the dataset).

The Corel dataset is the most popular and commonly used dataset to test the retrieval performance, MIT-Color dataset used for texture and color feature analysis and Brodtz dataset used for texture analysis.

Fig. 21 Comparison with other relevance feedback approaches for multimodal retrieval on UW dataset [49].