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						Multimedia content based retrieval slideshare.ppt
						https://www.slideshare.net/govintech1/multimedia-content-based-retrieval-slideshareppt
						
						 
						
						
						
						Multimedia content based retrieval slideshare.ppt - [PPTX ...
						https://vdocuments.net/multimedia-content-based-retrieval-slideshareppt.html
						In this presentation, an overview of the content based retrieval is presented along withthe different strategies in terms of syntactic and semantic indexing for retrieval. The matching techniquesused and learning methods employed are also analyzed.
						 
						
						
						
						Similarity Searching Techniques in Content-based …
						https://www.nara-wu.ac.jp/initiative-MPI/images/Kokusai.Gakkai/Yu%20Yi/ppt-MMM2007%201%2011-Yi.pdf
						
						 
						
						
						
						PPT – Audio Segmentation, Classification, and Retrieval ...
						https://www.powershow.com/view1/d32ca-ZDc1Z/Audio_Segmentation_Classification_and_Retrieval_powerpoint_ppt_presentation
						Content-based retrieval of audio - Need effective ways to browse by content through audio databases of growing sizes ... Spectrogram computed using STFT of 2048 samples with Hamming window of 1024 ... | PowerPoint PPT presentation | free to view
						 
						
						
						
						Features for Content-Based Audio Retrieval
						https://publik.tuwien.ac.at/files/PubDat_186351.pdf
						Content-based audio retrieval is an ill-posed problem (also known as inverse problem). In general, an ill-posed problem is concerned with the estimation of model parameters by the manipulation of observed data. In case of a retrieval task, model parameters are terms, properties and concepts that may represent 4.
						 
						
						
						
						Content-based audio classification and retrieval using the ...
						https://citeseerx.ist.psu.edu/showciting?cid=72581&start=10
						
						 
						
						
						
						A TEXT RETRIEVAL APPROACH TO CONTENT-BASED AUDIO …
						http://www.ideal.ece.utexas.edu/pdfs/164.pdf
						This paper presents a novel approach to robust, content-based retrieval of digital music. We formulate the hash-ing and retrieval problems analogously to that of text re-trieval and leverage established results for this unique ap-plication. Accordingly, songs are represented as a ”Bag-of-Audio-Words” and similarity calculations follow directly
						 
						
						
							
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