Sentence examples for visual datasets from inspiring English sources

This solution is compared with state-of-the-art approaches using two visual datasets: PKLot, already existing in literature, and CNRPark-EXT.

The scope of research covering large-scale visual datasets is broad.

To the best of our knowledge, processing such large-scale hybrid visual datasets on a single computer in a few days is unprecedented.

3D modeling first needs to establish pairwise epipolar geometry relationships within photo collections, thus provides a good example for mining inter-element connections within unordered visual datasets.

To address this challenge, we first propose to represent video contents using a histogram representation of iconic imagery attained from relevant visual datasets.

For visual dataset, we can further improve the DDBN performance with much larger and deeper architecture.

The more expensive keyframe selection method [18] generated fewer keyframes but a similar number of iconics, which means it summarized the visual dataset with fewer iconic images.

Iconic images, as used in Frahm et al. [6] and Heinly et al. [7], provide a compact yet informative summarization of the common visual elements occurring within a visual dataset.

Using a large visual dataset of traffic signs and their ground truth, they showed that the joint representation of texture and color in HOG + Color histograms with multiple linear SVM classifiers result in the best performance for classification of multiple categorizes of traffic signs.

In the dataset, visual odometry dataset is provided.

Using this generative model, we are able to construct a synthetic audio-visual dataset, namely Sound-20K, for object perception tasks.