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Isomap is an important dimension reduction method for clustering data with relatively large features. Isomap uses geodesic distance instead of Euclidean distance to reflect geometry of the underlying manifold, while it ignores the classification ...
We present a novel algorithm for 3D reconstruction in this paper, converting incremental 3D reconstruction to an optimization problem by combining two feature-enhancing geometric priors and one photometric consistency constraint under the Bayesian ...
The fuzzy measure of competitiveness criteria can be used to enlighten policy making for enhancing national competitiveness. However, fuzzy densities and interactions among criteria are usually unknown or uncertain for implications thus making analysis ...
Cooperation among agents is critical for agents' Artificial Intelligence (AI). In multi-agent system (MAS), agents cooperate with each other for long-term return and build such partnership in most of the time. However, the partnership could be broken ...
The detection of moving objects is a critical first step in video surveillance. Numerous background subtraction, frame differencing, optical flow algorithms and a number of post-processing techniques (including noise removal, binary morphological ...
The article presents an original approach to optical character recognition (OCR) used in real environments, such as gas- and electricity-meters, where the quantity of noise is sometimes as large as the quantity of good signal. This approach uses two ...
The cosine and Tanimoto similarity measures are often and successfully applied in classification, clustering and ranking in chemistry, biology, information retrieval, and text mining. A basic operation in such tasks is identification of neighbors. This ...
This paper describes an approach for the camera motion estimation and moving object detection via tracking of the local image regions through the image sequence. The propose algorithm consists of two parts. First image of the sequence is used to compose ...
Our intelligent decision-making approach (IDMA) is an instance of cognitive computing. It applies causality as common sense reasoning and fuzzy logic as a representation for qualitative knowledge. Our IDMA collects raw knowledge of humans through ...
Theory of mind based reasoning is crucial for humans that interact with each other. Also in the domain of multi-agent systems the importance of theory of mind based reasoning has been stressed, for instance in the process of selecting appropriate ...
Data split into batches is very common in real-world applications. In speech recognition and handwriting identification, the batches are different people. In areas like oil spill detection and train wheel failure prediction, the batches are the ...
Most available motif discovery algorithms in real-valued time series find approximately recurring patterns of a known length without any prior information about their locations or shapes. In this paper, a new motif discovery algorithm is proposed that ...
Though there exist a lot of cluster ensemble approaches, few of them consider how to degrade the effect of noisy attributes in the dataset. In the paper, we propose a new cluster ensemble framework, named as double self-organizing map based cluster ...
The classification of diffuse lung opacities in high-resolution computed tomography(HRCT) images is an important step for developing a computer-aided diagnosis(CAD) system. In designing the CAD system for classifying diffuse lung opacities in HRCT ...
Rank-based algorithms provide a promising approach for outlier detection, but currently used rank-based measures of outlier detection suffer from two deficiencies: first they assign a large value to an object near a cluster whose density is high even ...
Phishing --- a hotbed of multibillion dollar underground economy --- has become an important cybersecurity problem. The centralized blacklist approach used by most web browsers usually fails to detect zero-day attacks, leaving the ordinary users ...
This paper proposes a method for enhancing accuracy of point clouds which are generated from small baseline of sequence images. The main contributions are threefold: First, the constraints of image pair-wise are computed based on invariant feature. The ...
State-space search redundancy, that is, multiple explorations of the same state, is an inherent problem in many heuristic search algorithms. It is prevalent in constructive multi-start algorithms. Record-keeping mechanisms, however, can minimize ...
We propose a framework for recognizing actions or gestures by modelling variations of the corresponding shape postures with respect to each action class thereby removing the need for normalization for the speed of motion. The three main aspects are the ...
The fastest Learning Automata (LA) algorithms currently available come from the family of estimator algorithms. The Pursuit algorithm (PST), a pioneering scheme in the estimator family, obtains its superior learning speed by using Maximum Likelihood (ML)...