
Drowsiness Detection Based On Driver Temporal Behavior Using a New Developed Dataset
Driver drowsiness detection has been the subject of many researches in t...
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Deep Learning for Neuroimagingbased Diagnosis and Rehabilitation of Autism Spectrum Disorder: A Review
Accurate diagnosis of Autism Spectrum Disorder (ASD) is essential for ma...
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A Novel LowComplexity Framework in UltraWideband Imaging for Breast Cancer Detection
In this research work, a novel framework is pro posed as an efficient s...
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Transferrable Plausibility Model  A Probabilistic Interpretation of Mathematical Theory of Evidence
This paper suggests a new interpretation of the DempsterShafer theory i...
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On the Discrepancy Between Kleinberg's Clustering Axioms and kMeans Clustering Algorithm Behavior
This paper investigates the validity of Kleinberg's axioms for clusterin...
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On Seeking Consensus Between Document Similarity Measures
This paper investigates the application of consensus clustering and meta...
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Fixpoint Approximation of Strategic Abilities under Imperfect Information
Model checking of strategic ability under imperfect information is known...
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On the Existence of Kernel Function for KernelTrick of kMeans
This paper corrects the proof of the Theorem 2 from the Gower's paper [p...
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How good is the Shapley valuebased approach to the influence maximization problem?
The Shapley value has been recently advocated as a method to choose the ...
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Asymptotic consistency and order specification for logistic classifier chains in multilabel learning
Classifier chains are popular and effective method to tackle a multilab...
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Feature ranking for multilabel classification using Markov Networks
We propose a simple and efficient method for ranking features in multil...
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Random Graphs for Performance Evaluation of Recommender Systems
The purpose of this article is to introduce a new analytical framework d...
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Random Graph Generator for Bipartite Networks Modeling
The purpose of this article is to introduce a new iterative algorithm wi...
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Semantic classifier approach to document classification
In this paper we propose a new document classification method, bridging ...
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Grammatical Case Based ISA Relation Extraction with Boosting for Polish
Patternbased methods of ISA relation extraction rely heavily on so cal...
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SOMRS: a multirobot system architecture based on the SOA paradigm and ontology
A generic architecture for a class of distributed robotic systems is pre...
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Analysis and Code Design for the Binary CEO Problem under Logarithmic Loss
In this paper, we propose an efficient coding scheme for the binary Chie...
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Binary CEO Problem under LogLoss with BSC TestChannel Model
In this paper, we propose an efficient coding scheme for the twolink bi...
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LDPC Codes over Gaussian Multiple Access Wiretap Channel
We study the problem of twouser Gaussian multiple access channel (GMAC)...
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Successive WynerZiv Coding for the Binary CEO Problem under LogLoss
An llink binary CEO problem is considered in this paper. We present a p...
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Boosting algorithms for uplift modeling
Uplift modeling is an area of machine learning which aims at predicting ...
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A Fast Text Similarity Measure for Large Document Collections using Multireference Cosine and Genetic Algorithm
One of the important factors that make a search engine fast and accurate...
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Multireference Cosine: A New Approach to Text Similarity Measurement in Large Collections
The importance of an efficient and scalable document similarity detectio...
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A Machine Learning Approach to Persian Text Readability Assessment Using a Crowdsourced Dataset
An automated approach to text readability assessment is essential to a l...
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Successive WynerZiv Coding for the Binary CEO Problem under Logarithmic Loss
The Llink binary Chief Executive Officer (CEO) problem under logarithmi...
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Augmentation Scheme for Dealing with Imbalanced Network Traffic Classification Using Deep Learning
One of the most important tasks in network management is identifying dif...
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Uncertainty Principle in Distributed MIMO Radars
Radar uncertainty principle indicates that there is an inherent invarian...
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Trajectory Optimization for Robust Humanoid Locomotion with SampleEfficient Learning
Trajectory optimization (TO) is one of the most powerful tools for gener...
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Selection consistency of Lassobased procedures for misspecified highdimensional binary model and random regressors
We consider selection of random predictors for highdimensional regressi...
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Improving Lasso for model selection and prediction
It is known that the Thresholded Lasso (TL), SCAD or MCP correct intrins...
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Clustering of Medical FreeText Records Based on Word Embeddings
Is it true that patients with similar conditions get similar diagnoses? ...
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Robust Humanoid Locomotion Using Trajectory Optimization and SampleEfficient Learning
Trajectory optimization (TO) is one of the most powerful tools for gener...
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Text as Environment: A Deep Reinforcement Learning Text Readability Assessment Model
Evaluating the readability of a text can significantly facilitate the pr...
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SemiSupervised Neural System for Tagging, Parsing and Lematization
This paper describes the ICS PAS system which took part in CoNLL 2018 sh...
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Universal Coding and Prediction on MartinLöf Random Points
We perform an effectivization of classical results concerning universal ...
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Unlucky Explorer: A Complete nonOverlapping Map Exploration
Nowadays, the field of Artificial Intelligence in Computer Games (AI in ...
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BetweenDomain Instance Transition Via the Process of Gibbs Sampling in RBM
In this paper, we present a new idea for Transfer Learning (TL) based on...
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ARCNet: Activity Recognition Through Capsules
Human Activity Recognition (HAR) is a challenging problem that needs adv...
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Preintegrated IMU Features For Efficient Deep Inertial Odometry
MEMS Inertial Measurement Units (IMUs) are inexpensive and effective sen...
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A Novel Method For Designing Transferable Soft Sensors And Its Application
In this paper, a new approach is proposed for designing transferable sof...
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Single Object Tracking through a Fast and Effective SingleMultiple Model Convolutional Neural Network
Object tracking becomes critical especially when similar objects are pre...
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Investigating Text Simplification Evaluation
Modern text simplification (TS) heavily relies on the availability of go...
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A Sparse Structure Learning Algorithm for Bayesian Network Identification from Discrete HighDimensional Data
This paper addresses the problem of learning a sparse structure Bayesian...
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Dynamic Models of Spherical Parallel Robots for ModelBased Control Schemes
In this paper, derivation of different forms of dynamic formulation of s...
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