Xinhai tailings dry stacking technology is mainly applied to the dewatering and concentrating of mineral tailings in the mineral processing plants. To reach the aim of tailings dry stacking and avoiding environmental pollution, it is the essential technology of green mine.
Phosphate Flotation Product Line is applied for complex structure phosphate with fine particle distribution, closed embeddedness relationship, difficult monomer dissociation, etc.
Barite is fragile and like a big tube. The separation methods of Xinhai are generally gravity separation, magnetic separation and flotation.
Alluvial gold processing solution mainly applies to processing alluvial gold with a large volume of gangue minerals. Alluvial gold processing is a set of mining processes, including crushing and screening, desliming stage, separating stage, etc.
copy detection scheme and a Visual CharacterString (VCS) descriptor for SSM matching. SSM which exploits the spatial and temporal information in a video clip is extracted from exhaustive calculation of distances between the frames. The SSM based method treats the video clip as a whole and transforms the temporal selfsimilarity into a matrix.
Mining Spatial and SpatioTemporal Patterns in Scientific Data Abstract Data mining is the process of discovering hidden and meaningful knowledge in a data set. It has been successfully applied to many reallife problems for instance web personalization network intrusion detection and
Home Browse by Title Proceedings ICME'09 Robust copy detection by mining temporal selfsimilarities. ARTICLE . Robust copy detection by mining temporal selfsimilarities. Share on. Authors Zhipeng Wu. Graduate University of Chinese Academy of Sciences Beijing China.
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Robust copy detection by mining temporal selfsimilarities. June 2009 DOI 10.1109/ICME.2009.5202556. Source DBLP Conference Proceedings of the 2009 IEEE International Conference on Multimedia
We propose a new contentbased video copy detection algorithm. The proposed algorithm creates signatures that capture the spatial and temporal features of videos. These spatiotemporal signatures enable the algorithm to provide both high precision and recall. In addition these signatures require small storage and are easy to compute and compare.
Anomaly Detection Using Temporal Data Mining in a Smart Home Environment V. Jakkula and D.J. Cook Washington State University EME 121 Spokane Street Pullman WA 99164 USA Office 5093354985 Fax 5093353818 Email [email protected]
Robust copy detection by mining temporal selfsimilarities This paper introduces a SelfSimilarity Matrix (SSM) based video copy detection scheme and a Visual CharacterString (VCS) descriptor for SSM matching. SSM which exploits the spatial and temporal information in a video clip is extracted from exhaustive calculation of distances between the frames.
The proposed descriptor is succinct in concept compact in structure robust for rotation like transformations and fast to compute. Experiments on the CIVR07 Copy Detection Corpus and the Video Transformation Corpus show improved performances both on matching quality and executive time compared to the pervious approaches.
This paper introduces a selfsimilarity matrix (SSM) based video copy detection scheme and a visual characterstring (VCS) descriptor for SSM matching. SSM which exploits the spatial and temporal information in a video clip is extracted from exhaustive calculation of distances between the frames. The SSM based method treats the video clip as a whole and transforms the temporal selfsimilarity into
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