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{{Short description|Algorithm to detect local features in images}} {{Feature detection (computer vision) navbox}} ...

...each hypothesis give a most probable action. This technique is widely used in the area of [[artificial intelligence]]. ...texture and so on, which can be detected by [[feature detection (computer vision)|feature detection]] methods. ...

{{Short description|Family of computer vision models designed for efficient inference}} ...] (CNNs) for [[computer vision]] published by researchers at [[Google AI]] in 2019.<ref name=":0">{{Citation |last1=Tan |first1=Mingxing |title=Efficient ...

...performance of the SIFT algorithm. In fact, ranking techniques can be used in key point localization or descriptor generation of the original SIFT algori ...; "Rank-SIFT: Learning to rank repeatable local interest points", Computer Vision and Pattern Recognition (CVPR), 2011</ref> ...

{{Short description|Machine Learning concept}} ...w |first3=I. |date=2016 |title=Practical black-box attacks against machine learning |class=cs.CR |eprint=1602.02697}}</ref> ...

...tyle_Transfer_CVPR_2016_paper.html |conference=IEEE Conference on Computer Vision and Pattern Recognition (CVPR) |pages=2414–2423}}</ref> ...ref name=":0">{{Cite book |last1=Zhang |first1=Aston |title=Dive into deep learning |last2=Lipton |first2=Zachary |last3=Li |first3=Mu |last4=Smola |first4=Ale ...

{{Short description|Family of computer vision models designed for efficient inference on mobile devices}} ...ned for [[image classification]], [[object detection]], and other computer vision tasks. They are designed for small size, low latency, and low power consump ...

...0 6.png|thumb|Flattening a (3rd-order) tensor. The tensor can be flattened in three ways to obtain matrices comprising its mode-0, mode-1, and mode-2 vec In [[multilinear algebra]], '''mode-m flattening'''{{r|Vasilescu2009|vasilescu ...

...originally developed by Edward Rosten and Tom Drummond, and was published in 2006.<ref> |title=Computer Vision – ECCV 2006 ...

{{Short description|Supervised learning of a similarity function}} ...|similar]] or related two objects are. It has applications in [[ranking]], in [[recommendation systems]], visual identity tracking, face verification, an ...

...ref name=":2">{{Cite book |last1=Zhang |first1=Aston |title=Dive into deep learning |last2=Lipton |first2=Zachary |last3=Li |first3=Mu |last4=Smola |first4=Ale In 2014, a team at Google developed the GoogLeNet architecture, an instance of ...

{{Short description|Reinforcement learning method}} ...f error-driven learning in simple two-layer networks from a discriminative learning perspective |url=https://doi.org/10.3758/s13428-021-01711-5 |journal=Behavi ...

'''Shrinkage fields''' is a [[random field]]-based [[machine learning]] technique that aims to perform high quality [[Image restoration by artifi The learning objective function is defined as <math>J\left({\mathrm{\Theta }}_{t}\right) ...

...s function]] widely used in [[One-shot learning (computer vision)|one-shot learning]], a setting where models are trained to generalize effectively from limite | publisher = IEEE Computer Society ...

{{Short description|Supervised machine learning techniques}} {{Machine learning|Problems}} ...

{{Short description|Computer vision algorithm}} ...and corners.<ref name="dey"/> Since then, it has been improved and adopted in many algorithms to preprocess images for subsequent applications. ...

...ef name="Goodfellow">{{Cite book |last1=Goodfellow |first1=Ian |title=Deep Learning |last2=Bengio |first2=Yoshua |last3=Courville |first3=Aaron |date=2016 |pub ...name="Zhang">{{Cite book |last1=Zhang |first1=Aston |title=Dive into deep learning |last2=Lipton |first2=Zachary |last3=Li |first3=Mu |last4=Smola |first4=Ale ...

...Multivariate Time Series] ''Physical Review Letters'' 103, 214101.</ref> in [[statistics]] is a [[blind source separation]] [[algorithm]] which factori ...SA allows the separation of the stationary from the non-stationary sources in an observed time series. ...

...tist and Distinguished Professor at [[University of Surrey]], specialising in [[pattern recognition]] and machine intelligence. ...He joined [[Surrey University]] in 1986 and became Distinguished Professor in 2004. ...

...ptometry]], with an affiliated appointment in [[Electrical Engineering and Computer Sciences]]. He is also the Director of the [[Redwood Center for Theoretical ...hology, [[Cornell University]] and Center for Biological and Computational Learning, [[Massachusetts Institute of Technology]].<ref>{{Cite web |title=Bruno's c ...