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pro vyhledávání: '"Michael W. Spratling"'
Autor:
Bo Gao, Michael W. Spratling
Publikováno v:
Sensors, Vol 22, Iss 17, p 6658 (2022)
Finding a template in a search image is an important task underlying many computer vision applications. This is typically solved by calculating a similarity map using features extracted from the separate images. Recent approaches perform template mat
Externí odkaz:
https://doaj.org/article/72570f743c434ed5ac98b3a348895092
Autor:
Bo Gao, Michael W. Spratling
Publikováno v:
The Visual Computer. 39:2081-2095
Many current trackers utilise an appearance model to localise the target object in each frame. However, such approaches often fail when there are similar-looking distractor objects in the surrounding background, meaning that target appearance alone i
Autor:
Bo Gao, Michael W. Spratling
Publikováno v:
Lecture Notes in Electrical Engineering ISBN: 9789811669620
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e1c39450d6709f793184aadf3ec22b59
https://doi.org/10.1007/978-981-16-6963-7_31
https://doi.org/10.1007/978-981-16-6963-7_31
Autor:
Bo Gao, Michael W. Spratling
Publikováno v:
Signal Processing. 199:108628
Publikováno v:
Kartoglu, I E & Spratling, M W 2018, ' Two collaborative filtering recommender systems based on sparse dictionary coding ', KNOWLEDGE AND INFORMATION SYSTEMS, vol. 57, no. 3, pp. 709-720 . https://doi.org/10.1007/s10115-018-1157-2
This paper proposes two types of recommender systems based on sparse dictionary coding. Firstly, a novel predictive recommender system that attempts to predict a user’s future rating of a specific item. Secondly, a top-n recommender system which fi
Autor:
Michael W Spratling
Publikováno v:
Frontiers in Computational Neuroscience, Vol 2 (2008)
A simple variation of the standard biased competition model is shown, via some trivial mathematical manipulations, to be identical to predictive coding. Specifically, it is shown that a particular implementation of the biased competition model, in wh
Externí odkaz:
https://doaj.org/article/82c59b2458e74a4baf7bfe027b6822c0
Autor:
Michael W. Spratling, Wasif Muhammad
Publikováno v:
Muhammad, W & Spratling, M W 2017, ' A neural model for eye–head–arm coordination ', Advanced Robotics, vol. 31, no. 12, pp. 650-663 . https://doi.org/10.1080/01691864.2017.1315319
The coordinated movement of the eyes, the head and the arm is an important ability in both animals and humanoid robots. To achieve this, the brain and the robot control system need to be able to perform complex non-linear sensory-motor transformation
Autor:
Michael W. Spratling
Publikováno v:
Spratling, M W 2019, ' Fitting Predictive Coding to the Neurophysiological Data ', Brain research, vol. 1720, 146313, pp. 1-8 . https://doi.org/10.1016/j.brainres.2019.146313
Recent neurophysiological data showing the effects of locomotion on neural activity in mouse primary visual cortex has been interpreted as providing strong support for the predictive coding account of cortical function. Specifically, this work has be
Autor:
Michael W. Spratling
Publikováno v:
Cognitive Computation
Spratling, M W 2017, ' A Hierarchical Predictive Coding Model of Object Recognition in Natural Images ', Cognitive Computation, vol. 9, no. 2, pp. 151–167 . https://doi.org/10.1007/s12559-016-9445-1
Spratling, M W 2017, ' A Hierarchical Predictive Coding Model of Object Recognition in Natural Images ', Cognitive Computation, vol. 9, no. 2, pp. 151–167 . https://doi.org/10.1007/s12559-016-9445-1
Predictive coding has been proposed as a model of the hierarchical perceptual inference process performed in the cortex. However, results demonstrating that predictive coding is capable of performing the complex inference required to recognise object
Autor:
Michael W. Spratling
Publikováno v:
Spratling, M W 2016, ' A neural implementation of Bayesian inference based on predictive coding ', CONNECTION SCIENCE, vol. 28, no. 4, pp. 346-383 . https://doi.org/10.1080/09540091.2016.1243655
Predictive coding (PC) is a leading theory of cortical function that has previously been shown to explain a great deal of neurophysiological and psychophysical data. Here it is shown that PC can perform almost exact Bayesian inference when applied to