Results 31 to 40 of about 253,866 (247)
Text Recovery via Deep CNN-BiLSTM Recognition and Bayesian Inference
IEEE Access, 2018 Image inpainting is an essential process of semantically filling the missing holes in a corrupt image. However, concurrent methods cannot semantically recover some self-described objects, such as a text instance.
Libin Jiao, Hao Wu, Haodi Wang, R. Bie
semanticscholar +1 more source
Marginal and simultaneous predictive classification using stratified graphical models [PDF]
, 2014 An inductive probabilistic classification rule must generally obey the principles of Bayesian predictive inference, such that all observed and unobserved stochastic quantities are jointly modeled and the parameter uncertainty is fully acknowledged ...
Corander, Jukka +3 more
core +1 more source
Multi-task Image Classification via Collaborative, Hierarchical Spike-and-Slab Priors
, 2015 Promising results have been achieved in image classification problems by exploiting the discriminative power of sparse representations for classification (SRC).
Dao, Minh +5 more
core +1 more source
Gaussian Processes with Context-Supported Priors for Active Object Localization
, 2017 We devise an algorithm using a Bayesian optimization framework in conjunction with contextual visual data for the efficient localization of objects in still images.
Jedynak, Bruno +3 more
core +1 more source
SERKET: An Architecture for Connecting Stochastic Models to Realize a Large-Scale Cognitive Model
, 2017 To realize human-like robot intelligence, a large-scale cognitive architecture is required for robots to understand the environment through a variety of sensors with which they are equipped.
Nagai, Takayuki +2 more
core +2 more sources
PolyChord: nested sampling for cosmology
, 2015 PolyChord is a novel nested sampling algorithm tailored for high dimensional parameter spaces. In addition, it can fully exploit a hierarchy of parameter speeds such as is found in CosmoMC and CAMB.
Handley, W. J. +2 more
core +1 more source
FEBS Open Bio, EarlyView.This protocol paper outlines methods to establish the success of a time‐resolved serial crystallographic experiment, by means of statistical analysis of timepoint data in reciprocal space and models in real space. We show how to amplify the signal from excited states to visualise structural changes in successful experiments.
Jake Hill +4 more
wiley +1 more source
Shared Genetic Effects and Antagonistic Pleiotropy Between Multiple Sclerosis and Common Cancers
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Epidemiologic studies have reported inconsistent altered cancer risk in individuals with multiple sclerosis (MS). Factors such as immune dysregulation, comorbidities, and disease‐modifying therapies may contribute to this variability.
Asli Buyukkurt +5 more
wiley +1 more source
A review of domain adaptation without target labels
, 2019 Domain adaptation has become a prominent problem setting in machine learning and related fields. This review asks the question: how can a classifier learn from a source domain and generalize to a target domain?
Kouw, Wouter M., Loog, Marco
core +1 more source
Clustering Algorithm Reveals Dopamine‐Motor Mismatch in Cognitively Preserved Parkinson's Disease
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To explore the relationship between dopaminergic denervation and motor impairment in two de novo Parkinson's disease (PD) cohorts. Methods n = 249 PD patients from Parkinson's Progression Markers Initiative (PPMI) and n = 84 from an external clinical cohort.
Rachele Malito +14 more
wiley +1 more source