• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.4
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• pp.161-166
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• 2018

In this paper, we propose a method for the random selection of pooling operations for the regularization and reduction of cross validation in convolutional neural networks. The pooling operation in convolutional neural networks is used to reduce the size of the feature map and for its shift invariant properties. In the existing pooling method, one pooling operation is applied in each pooling layer. Because this method fixes the convolution network, the network suffers from overfitting, which means that it excessively fits the models to the training samples. In addition, to find the best combination of pooling operations to maximize the performance, cross validation must be performed. To solve these problems, we introduce the probability concept into the pooling layers. The proposed method does not select one pooling operation in each pooling layer. Instead, we randomly select one pooling operation among multiple pooling operations in each pooling region during training, and for testing purposes, we use probabilistic weighting to produce the expected output. The proposed method can be seen as a technique in which many networks are approximately averaged using a different pooling operation in each pooling region. Therefore, this method avoids the overfitting problem, as well as reducing the amount of cross validation. The experimental results show that the proposed method can achieve better generalization performance and reduce the need for cross validation.

• Journal of Information Processing Systems
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• v.15 no.5
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• pp.1179-1191
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• 2019

We design an ingenious view-pooling method named learning-based multiple pooling fusion (LMPF), and apply it to multi-view convolutional neural network (MVCNN) for 3D model classification or retrieval. By this means, multi-view feature maps projected from a 3D model can be compiled as a simple and effective feature descriptor. The LMPF method fuses the max pooling method and the mean pooling method by learning a set of optimal weights. Compared with the hand-crafted approaches such as max pooling and mean pooling, the LMPF method can decrease the information loss effectively because of its "learning" ability. Experiments on ModelNet40 dataset and McGill dataset are presented and the results verify that LMPF can outperform those previous methods to a great extent.

• Journal of Navigation and Port Research
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• v.38 no.4
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• pp.399-407
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• 2014

Due to the increase of container terminals, as the volume of terminals become distributed, the competition of preserving existing volume and inviting new volume are becoming fierce, and various ways for processing terminal volume and inviting volume are being sought. Container terminal efforts to maximize efficiency in order to improve the volume handling capability and productivity by both expansion of the latest equipment and development of the latest terminal system. There are a variety of factors that influence the improvement of productivity at container terminals. Among them, in the case of yard transfer equipment, if it were to convert from the method of a Yard Tractor(YT) being fixed allocated to a certain Gantry Cranes(GC) to a Pooling System that processes in a method that properly distributes and allocates a Yard Tractor(YT) to multiple Gantry Cranes(GC), the terminal productivity and the fusibility of YT may be increased. The KPI which is an indicator for the productivity at container terminals is GC productivity and since GC productivity cannot exceed the speed of physical GC operations, a Pooling System is applied to increase productivity which its meaning and effect is massive. Here in the Report, we produce the Pooling Algorithm system to improve the efficiency of the transported equipments in container terminal which is actually applying for this method and have compared Non pooling system with Pooling system in the fields. By introducing a transfer equipment pooling system and enhancing the productivity compared to other terminals, it may become an essential factor for increasing the continuous service quality and profitability in terms of terminal business.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.395-398
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• 2005

Genetic association case-control studies using DNA pools are efficient ways of detecting association between a marker allele and disease status. DNA pooling is an efficient screening method for locating susceptibility genes associated with the disease. However, DNA pooling is efficient only when allele frequency estimation is done precisely and accurately. Through the evaluation of empirical type I errors and empirical powers by simulation, we will evaluate the methods that correct for preferential amplification of nucleotides when estimating the allele frequency of single-nucleotide polymorphisms.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.3
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• pp.375-381
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• 2023

Fully homomorphic encryption enables algebraic operations on encrypted data, and recently, methods for approximating non-algebraic operations such as the maximum function have been studied. However, precise approximation of max-pooling operations for four or more numbers have not been researched yet. In this study, we propose a precise max-pooling approximation method using the composition of approximate polynomials of the maximum function and theoretically analyze its precision. Experimental results show that the proposed approximate max-pooling has a small amortized runtime of less than 1ms and high precision that matches the theoretical analysis.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.11a
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• pp.29-32
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• 2020

Due to the lack of improper image acquisition process, noise induction is an inevitable step. As a result, objective image quality assessment (IQA) plays an important role in estimating the visual quality of noisy image. Plenty of IQA methods have been proposed including traditional signal processing based methods as well as current deep learning based methods where the later one shows promising performance due to their complex representation ability. The deep learning based methods consists of several convolution layers and down sampling layers for feature extraction and fully connected layers for regression. Usually, the down sampling is performed by using max-pooling layer after each convolutional block. We reveal that this max-pooling causes information loss despite of knowing their importance. Consequently, we propose a better IQA method that replaces the max-pooling layers with strided convolutions to down sample the feature space and since the strided convolution layers have learnable parameters, they preserve optimal features and discard redundant information, thereby improve the prediction accuracy. The experimental results verify the effectiveness of the proposed method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.7
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• pp.2603-2609
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• 2010

Currently at port, various trials about the improvement of operating method for raising operation efficiency of transferring equipment are made, but if the delay is occurred to quay crane due to individual team method in YT operation, the problem which even arranged YT should stop the work. Therefore, this study installed wireless location determining device within yard and measured the location of YT with real-time. Also, in order to raise the location determination effect, we converted operating method into pooling operation method and arranged YT. Through this study, we can trace the movement of YT with real-time and the work control method which anlayzes and evaluates congestion of yard objectively is prepared.

• Journal of the Korea Society for Simulation
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• v.28 no.3
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• pp.25-40
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• 2019

Today, container terminals are fiercely competing to attract an increasing number of containers. As a way to improve terminal productivity, this study proposes two dispatching rules for yard truck allocation priorities. First, Multi-Attribute Dispatching Rule(MADR) is an allocation method to calculate the weighted sum of multiple factors affecting container terminal productivity and priority them. Especially, the workload of the quay crane was considered one of the factors to reduce the residence time of the ship. Second, Cycling Dispatching Rule(CDR) is the effective way to increase the number of double cycles that directly affect terminal productivity. To identify the effects of combinations of pooling and dispatching, a comparative experiments was performed on 8 scenarios that combined them. A simulation environment has been developed for experiments and the results have demonstrated that the combination of terminal level pooling and Multi-attribute Dispatching could be an excellent combination in KPIs consisting of GCR and delayed departure of ships, etc.

• Journal of Aerospace System Engineering
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• v.10 no.3
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• pp.63-69
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• 2016

The properties of composite materials, when compared to those of metallic materials, are highly variable due to many factors including the batch-to-batch variability of raw materials, the prepreg manufacturing process, material handling, part-fabrication techniques, ply-stacking sequences, environmental conditions, and test procedures. It is therefore necessary to apply reliable statistical-analysis techniques to obtain the design allowables of composite materials. A new composite-material qualification process has been developed by the Advanced General Aviation Transport Experiments (AGATE) consortium to yield the lamina-design allowables of composite materials according to standardized coupon-level tests and statistical techniques; moreover, the generated allowables database can be shared among multiple users without a repeating of the full qualification procedure by each user. In 2005, NASA established the National Center for Advanced Materials Performance (NCAMP) with the purpose of refining and enhancing the AGATE process to a self-sustaining level to serve the entire aerospace industry. In this paper, the statistical techniques and procedures for the generation of the allowables of aerospace composite materials will be discussed with a focus on the pooling-across-environments method.

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.160-166
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• 2007

HANTEC 2.0 (A Korean Test Collection) is distributed for evaluation of information retrieval systems. HANTEC 2.0 is consists of 120,000 documents, 50 topics(queries) and relevant information. The relevant information is constructed by pooling methods. The relevant information is very important for evaluation of information retrieval systems. So we would like to review of the relevant information by manual method. It will be show validation of pooling method and HANTEC relevant information. We make tool for manual review of relevant information and review of that. We review of relevant information between manual relevant information and HANTEC's. We review of pooling method and HANTEC relevant information. The manual relevant information will be use evaluation of information retrieval systems.