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Smart city is a connection of physical and social infrastructure together with the information technology to leverage the collective intelligence of the city. Cities will build huge data centres. Thes...
The explosive growth of spatial data and widespread use of spatial databases emphasize the need for the spatial data mining. Co-location patterns discovery is an important branch in spatial data minin...
This paper deals with lidar point cloud filtering and classification for modelling the Terrain and more generally for scene segmentation. In this study, we propose to use the well-known K-means cluste...
The paper proposed a method of weather classification based on cloud model and hierarchical clustering. Firstly, according to the weather sampling data from FY-2C images, cluster the brightness values...
This paper proposes a spatial clustering model based on self-organizing feature map and a composite distance measure, and studies the knowledge discovery from spatial database of spatial objects with ...
Cross-lingual document clustering (CLDC) is the task to automatically or-ganize a large collection of cross-lingual documents into groups considering con-tent or topic. Different from the tradition-al...
Speaker clustering is an important step in multi-speaker detection tasks and its performance directly affects the speaker detection performance. It is observed that the shorter t...
Light Detection and Ranging (LIDAR) systems have become a standard data collection technology for capturing object surface information and 3D modeling of urban areas. Although, LIDAR systems provide...
3D object extraction is one of the main interests and has lots of applications in photogrammetry and computer vision. In recent years, airborne laser-scanning has been accepted as an effective 3D da...
One of the fundamental steps in the transformation of the LIDAR data into the meaningful objects in urban area involves their segmentation into consistent units through a clustering process. Neverth...
This paper presents a subspace SVM ensemble algorithm for adaptive relevance feedback (RF) learning. Our method deals with the case that user’s relevance feedback examples are usually insufficient and...
We propose a robust hierarchical background subtraction technique which takes the spatial relations of neighboring pixels in a local region into account to detect objects in difficult conditions. Our ...
This paper describes our approach for the “Who Rated What” task in KDD Cup 2007 competition. Given the Netflix data set that consists of more than 100 million ratings between 1998 and 2005, this task ...
Many sports videos such as archery, diving and tennis have repetitive structure patterns. They are reliable clues to generate highlights, summarization and automatic annotation. In this paper, we pre...
In this paper, a speaker segmentation method based on log-likelihood ratio score (LLRS) over universal background model (UBM) and a speaker clustering method based on difference of log-likelihood scor...

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