Showing papers in "CAAI Transactions on Intelligence Technology in 2016"

TL;DR: The basic concepts, operations and characteristics on the rough set theory are introduced, and then the extensions of rough set model, the situation of their applications, some application software and the key problems in applied research for the roughSet theory are presented.

TL;DR: A new optical hand tracking sensor, LeapMotion, is used to perform a non-contact demonstration for robotic systems, and the fusion principles are developed to get the improved and corrected gesture recognition.

TL;DR: Comparisons of advantages and disadvantages of various background modeling methods in video analysis applications and then compared their performance in terms of quality and the computational cost are analyzed.

TL;DR: This paper summarizes and analyzes the background, significance, research status and key technology of unmanned driving and the research group also introduces some research on brain cognition of driving and sensor placement of intelligent vehicles, which offers more meaningful reference to push the study of unmanneddriving.

TL;DR: A taxonomy of GPLVM related models in terms of the various strategies that be used and a detailed formulations of the main GPLVMs that extensively developed based on the strategies described in the paper.

TL;DR: Considering the spatio-temporal feature of messages and social relationships among users, an overall social network search framework from the perspective of semantics based on existing researches is summarized.

TL;DR: Social computing, as the technical foundation of future computational smart societies, has the potential to improve the effectiveness of open-source big data usage, systematically integrate a variety of elements including time, human, resources, scenarios, and organizations in the current cyber-physical-social world, and establish a novel social structure with fair information, equal rights, and a flat configuration.

TL;DR: Empirical findings on tourist arrivals from nine overseas origins reveal that the proposed approach performs comparably with SVMs and can achieve better prediction accuracy than other forecasting techniques for most origins.

TL;DR: This work presents a novel approach called sequential Bag-of-Words, which captures temporal sequential structure by segmenting the entire action into sub-actions and shows that it is robust and outperforms most existing BoWs based classification approaches.

TL;DR: It is concluded that SVM-based classifiers outperform the traditional ones in terms of recognition accuracy and robustness property when the original clinical data is distorted with noise.

TL;DR: It is considered that the joint models, or end-to-end models, will be one important trend for developing Human-Computer dialogue systems.

TL;DR: An automatic, video-based algorithm for detecting hydraulic excavators and dump trucks based on inverse valley feature of mechanical arm and spatial-temporal reasoning for hydraulic excavator detection is presented.

TL;DR: A revised particle swarm optimization (PSO) algorithm is proposed to train the weights of NN and rules of FLC and the results show that using the proposed methods can obtain better control effect.

TL;DR: This paper proposes a shortest path algorithm based on community detection (SPCD) by integrating community detection algorithm with traditional search methods and improves the time efficiency and maintains the accuracy scale of the SP.

TL;DR: A framework for RGBD SLAM in low dynamic environment, which can maintain a map keeping track of the latest environment and be able to manage the map in date in dynamic or static environment with a noncumulative complexity and acceptable error level is proposed.

TL;DR: The distribution of STIPs is organized into a salient directed graph, which reflects salient motions and can be divided into a time salient directedgraph and a space salient directed graphs, aiming at adding spatio-temporal discriminant to BoVW.

TL;DR: The results show that, with the fuzzy force control strategy, the bone milling system can recognize all surgery states and halt the tool at the proper location, achieving satisfactory surgery performance.

TL;DR: It is shown that the robot can be localised by solving a non-linear optimisation problem formulated to minimise the Chamfer distance with respect to the robot location by the proposed algorithm.

TL;DR: A multi-objective optimization framework for ill-posed inverse problems in image processing is introduced and two case studies of sparse reconstruction and change detection are implemented.

TL;DR: This work exploits structural similarity of log files and proposes a similarity based Bayesian learning approach for semi-structured logs to improve the accuracy of fault classification and results show that this approach outperforms other learning approaches on structural log datasets.

TL;DR: This paper proposes a novel approach called Adaptive Region Boosting (ARB), which effectively improves the success rate and outperforms all the other related methods in various dynamical scenarios, and a new criterion, called biased entropy, is proposed to evaluate the difficult degree of a region.

TL;DR: An overview of the current state of this rapidly growing field in China is presented and Chinese research in theoretical foundations of EC,EC-based optimization, EC-based data mining, and EC- based real-world applications are summarized.

TL;DR: This paper proposes a three-stage approach to manifold alignment using discrete surface Ricci flow, which transforms the original intrinsic manifolds to hyper spheres using conformal mapping in the first stage, and then zooms these hyper spheres into the same scale and aligns them in the following stages.

TL;DR: An novel method to improve collaborative representation based classification, which integrates an absolute distance vector into the residuals solved by collaborative representation, which produced a more promising result of classification on both facial and non-facial images than original CRC method.

TL;DR: The basic concepts and principles of artificial psychology and artificial emotion are introduced, and the unified macro-model of the cross-disciplinary system architecture against the need-motivation-behavior framework is analyzed.

TL;DR: Crowdsourcing as the core to STA component in the development life cycle is applied and dynamic and static ranking models are proposed and rank computation architecture is presented to deal with the case when the number of tenants and components becomes huge.

TL;DR: It is proved that SVM as a classifier can also be used for localization and soft constrained Minimum Average Correlation Energy filter (soft constrained MACE) is proposed, which is more resistent to overfittings to training set than other variants of correlation filter.

TL;DR: In order to operate various constrained mechanisms with assistive robot manipulators, an interactive control algorithm is proposed that decouples motion and force control in the constrained frame, and modifies the motion velocity online.

TL;DR: A novel method to reduce the effects of this issue for image classification by producing a new representation of original image, which can enhance the importance of moderate pixel intensities and reduce the effect of larger or smaller pixel intensITIES.