eThread: a highly optimized machine learning-based approach to meta-threading and the modeling of protein tertiary structures. [PDF]
PLoS ONE, 2012 Template-based modeling that employs various meta-threading techniques is currently the most accurate, and consequently the most commonly used, approach for protein structure prediction.
Michal Brylinski, Daswanth Lingam
doaj +1 more source
Frontiers in Neuroscience, 2020 Epilepsy is an abnormal function disease of movement, consciousness, and nerve caused by abnormal discharge of brain neurons in the brain. EEG is currently a very important tool in the process of epilepsy research.
Tongguang Ni, Xiaoqing Gu, Cong Zhang
doaj +1 more source
Busting a myth with the Bayes Factor: Effects of letter bigram frequency in visual lexical decision do not reflect reading processes [PDF]
, 2017 Psycholinguistic researchers identify linguistic variables and assess if they affect cognitive processes. One such variable is letter bigram frequency, or the frequency with which a given letter pair co-occurs in an orthography.
Mulatti, Claudio, Schmalz, Xenia
core +1 more source
Person Re-identification by Local Maximal Occurrence Representation and Metric Learning [PDF]
, 2015 Person re-identification is an important technique towards automatic search of a person's presence in a surveillance video. Two fundamental problems are critical for person re-identification, feature representation and metric learning.
Hu, Yang +3 more
core +1 more source
Robust Bayesian target detection algorithm for depth imaging from sparse single-photon data [PDF]
, 2016 This paper presents a new Bayesian model and associated algorithm for depth and intensity profiling using full waveforms from time-correlated single-photon counting (TCSPC) measurements in the limit of very low photon counts (i.e., typically less than 20
Altmann, Yoann +4 more
core +2 more sources
A summary of the 2012 JHU CLSP Workshop on Zero Resource Speech Technologies and Models of Early Language Acquisition [PDF]
, 2013 We summarize the accomplishments of a multi-disciplinary workshop exploring the computational and scientific issues surrounding zero resource (unsupervised) speech technologies and related models of early language acquisition.
Bennett, Erin +26 more
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How to (better) find a perpetrator in a haystack
Journal of Big Data, 2019 In many real-world contexts, there is a pressing need to automatically screen for potential perpetrators, such as school shooters, whose prevalence in the population is extremely low.
Yair Neuman +2 more
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Probabilistic models for prediction of the yield stress of rebars and compressive strength of concrete based on Bayesian linear regression [PDF]
مهندسی عمران شریفThis paper proposes probabilistic models for predicting the yield stress of reinforcing steel bars and the compressive strength of concrete used in Iran’s construction industry. The importance of this research stems from the recognition that the strength
H.R. Noorbala Tafti, M. Mahsuli
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Bayesian Diffusion Models for 3D Shape Reconstruction [PDF]
Computer Vision and Pattern RecognitionWe present Bayesian Diffusion Models (BDM), a prediction algorithm that performs effective Bayesian inference by tightly coupling the top-down (prior) information with the bottom-up (data-driven) procedure via joint diffusion processes.
Haiyang Xu +6 more
semanticscholar +1 more source
One-shot learning of object categories [PDF]
, 2006 Learning visual models of object categories notoriously requires hundreds or thousands of training examples. We show that it is possible to learn much information about a category from just one, or a handful, of images.
Fergus, Rob, Li, Fei-Fei, Perona, Pietro
core +2 more sources