We consider closed pattern mining from distributed multi-relational databases, especially focusing on its efficient implementation. Given a set of local databases (horizontal partitions), we first compute their sets o...
详细信息
ISBN:
(纸本)9781479959556
We consider closed pattern mining from distributed multi-relational databases, especially focusing on its efficient implementation. Given a set of local databases (horizontal partitions), we first compute their sets of closed patterns (concepts) using a closed pattern mining algorithm tailored to multi-relational data mining (MRDM). We then generate the set of closed patterns in the global database by utilizing the merge (or subposition) operator, studied in the field of Formal Concept Analysis. Since the computational complexity of MRDM increases compared with the conventional itemset mining, we propose some methods for improving the overall computations. We also present some experimental results using a distributed computation environment based on the MapReduce framework, which shows the effectiveness of the proposed methods.
This paper describes a special-purpose neural computing system for face identification. The system architecture and hardware implementation are introduced in detail. An algorithm based on biomimetic pattern recognitio...
详细信息
ISBN:
(纸本)0780378989
This paper describes a special-purpose neural computing system for face identification. The system architecture and hardware implementation are introduced in detail. An algorithm based on biomimetic patternrecognition has been embedded. For the total 1200 tests for face identification, the false rejection rate is 3.7% and the false acceptance rate is 0.7%.
The Internet-based security soft-i-Robot is modeled using softcomputing paradigms for problem solving and decision-making in complex and ill-structured situations. soft-i-Robot monitors the workspace with multimedia ...
详细信息
ISBN:
(纸本)9781479925834
The Internet-based security soft-i-Robot is modeled using softcomputing paradigms for problem solving and decision-making in complex and ill-structured situations. soft-i-Robot monitors the workspace with multimedia devices and sensor using an Internet application program. The model has sensory subsystems such as Intruder detection which, detects intruder, captures image and sends to server, and an Obstacle Avoidance Unit to detect the objects in the path of the mobile robot. These multiple features with hybrid softcomputing techniques depart the developed soft-i-Robot from the existing developments, proving that the streaming technology-based approach greatly improves the sensibility of robot tele-operation. The relatively powerful online robots available today provoke the simple question, in terms of two competing goals: recognition accuracy and computing time. Improved recognition accuracy and reduced computing time for face recognition of the intruder is obtained using Morphological Shared Weight Neural Network. To obtain a collision-free optimized path, soft-i-Robot uses derivative free Genetic Algorithm. With rapid expansion of Robotics and softcomputing paradigms, robotic technology touches upon self-understanding of humans, socio-economic, legal and ethical issues leading to improved performance rate and information processing capabilities.
Theoretical results suggest that in order to learn complicated functions that can represent high-level features in the computer vision field, one may need to use deep architectures. The popular choice among scientists...
详细信息
ISBN:
(纸本)9783319590639;9783319590622
Theoretical results suggest that in order to learn complicated functions that can represent high-level features in the computer vision field, one may need to use deep architectures. The popular choice among scientists and engineers for modeling deep architectures are feed-forward Deep Artificial Neural Networks. One of the latest research areas in this field is the evolution of Artificial Neural Networks: NeuroEvolution. This paper explores the effect of evolving a Node Transfer Function and its parameters, along with the evolution of connection weights and an architecture in Deep Neural Networks for patternrecognition problems. The results strongly indicate the importance of evolving Node Transfer Functions for shortening the time of training Deep Artificial Neural Networks using NeuroEvolution.
Traditional sparse coding has been successfully applied in texture and image classification in the past years. Yet such kind of method neglects the influence of the signs of coding coefficients, which may cause inform...
详细信息
ISBN:
(纸本)9784990644109;9781467322164
Traditional sparse coding has been successfully applied in texture and image classification in the past years. Yet such kind of method neglects the influence of the signs of coding coefficients, which may cause information loss in the sequential max pooling. In this paper, we propose a novel coding strategy for ground-based cloud classification, which is named soft-signed sparse coding. In our method, a constraint on the signs is explicitly added to the objective function of traditional sparse coding model, which can effectively regulate the ratio between the number of positive and negative non-zero coefficients. As a result, the proposed method can not only obtain low reconstruction error but also consider the influence of the signs of coding coefficients. The strategy is verified on two challenging cloud datasets, and the experimental results demonstrate the superior performance of our method compared with previous ones.
In this paper we propose a new probabilistic approach to red eye detection and correction. It is based on stepwise refinement of a pixel-wise red eye probability map. Red eye detection starts with a fast non red eye r...
详细信息
ISBN:
(纸本)0769525210
In this paper we propose a new probabilistic approach to red eye detection and correction. It is based on stepwise refinement of a pixel-wise red eye probability map. Red eye detection starts with a fast non red eye region rejection step. A classification step then adjusts the probabilities attributed to the detected red eye candidates. The correction step finally applies a soft red eye correction based on the resulting probability map. The proposed approach is fast and allows achieving an excellent correction of strong red eyes while producing a still significant correction of weaker red eyes.
With the increase in age and diabetes-related eye diseases, there is a rising demand for systems which can efficiently screen and locate abnormalities in retinal images. In this paper, we propose a framework that util...
详细信息
ISBN:
(纸本)9784990644109;9781467322164
With the increase in age and diabetes-related eye diseases, there is a rising demand for systems which can efficiently screen and locate abnormalities in retinal images. In this paper, we propose a framework that utilizes a variant of the Maximally Stable Extremal Region method, termed C-MSER, to systematically detect various retinopathy pathologies such as microaneurysms, haemorrhages, hard exudates and soft exudates. Experiments on three real-world datasets show that C-MSER is effective for online screening of diabetic retinopathy.
In this paper we analyze Support Vector Machine (SVM) algorithm to the problem of chemical compounds screening with a desired activity, definition of hits. The support vector machine transforms the input data in an (u...
详细信息
ISBN:
(纸本)9783540695721
In this paper we analyze Support Vector Machine (SVM) algorithm to the problem of chemical compounds screening with a desired activity, definition of hits. The support vector machine transforms the input data in an (unknown) high dimensional feature space and the kernel technique is applied to calculate the inner-product of feature data. The problem of automatically tuning multiple parameters for patternrecognition SVMs using our new introduced kernel for chemical compounds is considered. This is done by simple eigen analysis method which is applied to the matrix of the same dimension as the kernel matrix to find the structure of feature data, and to find the kernel parameter accordingly. We characterize distribution of data by the principle component analysis method.
A novel method is presented to improve the object recognition performance of a biologically inspired model by learning class-specific feature codebook. The feature codebook is multi-class shared in the original model,...
详细信息
ISBN:
(纸本)9781424429271
A novel method is presented to improve the object recognition performance of a biologically inspired model by learning class-specific feature codebook. The feature codebook is multi-class shared in the original model, and the content proportion for different codeword type is set in uniform distribution. According to corresponding discriminability, the codebook content proportion is adjusted upon different codeword types (feature vector sizes and filter scales). The test results demonstrate that the codebooks built with proposed modification achieve higher total-length efficiency.
This paper deals with the comparison of two different approaches for multi-task patternrecognition problem-multi-label and multi-perspective. The experiment performed measured the hamming loss and mean accuracy of bo...
详细信息
ISBN:
(纸本)9783319262277;9783319262253
This paper deals with the comparison of two different approaches for multi-task patternrecognition problem-multi-label and multi-perspective. The experiment performed measured the hamming loss and mean accuracy of both classifiers, to judge which of these two better fit to this kind of problem.
暂无评论