For each patch we then apply an image feature extractor (for the experiments in this paper we use the SIFT [6] features) to derive a vector representation for patches after which we produce a visual vocabulary clustering vectors to L clusters using k‚Äìmeans, as is customary in the image processing community.
Sample text:```5 concentrations were computed for each participant using a hierarchical spatiotemporal model fit with a pragmatic estimation procedure described elsewhere [30,31].```
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Sample text:```…methods rely on some additional and often heuristic step to generate an initial solution, such as adversarially-trained neural networks [Conneau et al., 2018, Zhang et al., 2017a,b], robust self-learning [Artetxe et al., 2018b] or
5This can be easily verified by noting that the…```
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Sample text:```…with several action-based models of selective action that suggest turning one’s visual attention to an object or location in space may be the same process as preparing a movement to that object/location (e.g., Rizzolatti et al.1994; Tipper et al.1992; Welsh and Elliott 2004b; Welsh et al.1999).```
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Sample text:```The merging is based on the increase in the weighted-bycounts entropy [1] and is stopped by a threshold indicating the minimum number of training samples required to estimate a weight distribution.```
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Sample text:```In the first pass, we display the diffuse lobe of the BRDF through spherical harmonic environment map rendering [Ramamoorthi and Hanrahan 2001].```
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Sample text:```05, minimum cluster size 64 voxels) [Woo et al., 2014] for the primary analysis of regions showing increasing activity with distance from the home location.```
Sample intent: method
Sample text:```05, minimum cluster size 64 voxels) [Woo et al., 2014] for the primary analysis of regions showing increasing activity with distance from the home location.```
Sample intent: method



Sample text:```5 concentrations were computed for each participant using a hierarchical spatiotemporal model fit with a pragmatic estimation procedure described elsewhere [30,31].```
Sample intent: background



Sample text:```…methods rely on some additional and often heuristic step to generate an initial solution, such as adversarially-trained neural networks [Conneau et al., 2018, Zhang et al., 2017a,b], robust self-learning [Artetxe et al., 2018b] or
5This can be easily verified by noting that the…```
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Sample text:```Following past work, we show that such basis models can be learned from 2D annotations using techniques adapted from nonrigid structure from motion (SFM) [20, 19].```
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Sample text:```…with several action-based models of selective action that suggest turning one’s visual attention to an object or location in space may be the same process as preparing a movement to that object/location (e.g., Rizzolatti et al.1994; Tipper et al.1992; Welsh and Elliott 2004b; Welsh et al.1999).```
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Sample text:```Over the last few years, many different local interest point detectors (like Harris3D [16], Cuboid [6], Hessian [35] or Dense sampling [33]) and many spatio-temporal descriptors (like HOG [17], HOG3D [14], HOF [17], Cuboid [6] or ESURF [35]) have been proposed.```
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Sample text:```In this study, we used the Knowledge Map Concept Indexer (KMCI) (Denny et al., 2009), a general-purpose NLP engine, to process all paper titles from American Journal of Epidemiology (AJE).```
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Sample text:```Our results confi rm previous studies that reached the same conclusion (Boushey et al 1994; Vermeulen et al 2000; Till et al 2005; Marcucci et al 2005).```
Sample intent: result



Sample text:```The merging is based on the increase in the weighted-bycounts entropy [1] and is stopped by a threshold indicating the minimum number of training samples required to estimate a weight distribution.```
Sample intent: method



Sample text:```…largest features in the 150-ms amplitude spectrum correspond to a loss of spectral features previously attributed to hK (Rothschild et al., 1988; Dioumaev and Braiman, 1997a), and a gain of features previously attributed to hL (Rothschild et al., 1988; Walter and Braiman, 1994; Chon et al.,…```
Sample intent: method