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Yatagai et al. [5] presented a method that analyzes the correlation between browsing time and page information size.
Our representation model is build upon a method that analyzes the spatiotemporal relationships between music and use of space in popular dance styles [1].
We utilize a consensus-based clustering method that analyzes several clusters produced by different algorithms or the same algorithm with different parameters and combines them into a single clustering model.
You et al. [12] suggested a method that analyzes the results of 16 × 16 ME (motion estimation) of a macroblock according to the proposed decision model, to estimate whether the macroblock partition size should be further divided.
Then we propose a method that analyzes the description of the items positively evaluated by the users and extracts a vector representation of the words in these descriptions (word embeddings).
There are two approaches to prediction, a work study method that analyzes each task by breaking it into definable work elements and the second method is empirical and involves rating a number of maintainability factors against a checklist.
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A novel bioinformatic method that analyzed the strand-specificity of the data reduced this to 53,071 putative transcripts from 18,573 components.
Such ratings are imperfectly correlated with formal, computational methods that analyze signal to noise ratios.
This distinguishes See & Spray from other computer vision-based weed detection methods that analyze growth patterns and colors in patches of plants and makes it much more precise.
The need for cyber-COIN tools has increased interest in methods that analyze so-called "dark web" content.
Unlike many other text detection methods that analyze either shape or color, the proposed method combines both by integrating the SWT [8] and Nikolaou text-oriented color reduction [14] methods.
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