• The KIPS Transactions:PartB
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• v.15B no.4
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• pp.293-300
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• 2008

This paper takes a bottom-up attention module into consideration for digital image watermarking. A bottom-up attention module is employed to obtain the region of interest, and watermark information is embedded into the obtained region. Previous studies in digital image watermarking have been focused on the signal processing techniques, especially in waveform coding spreading watermarks over the entire target image. However, we notice that the third party's visual attention is usually concentrated on a few regions in an image but not on all of them. These regions are easy to be the target of attacks. If watermark information is inserted into these regions from the beginning, it can be detected with high correlation. Various kinds of images are tested, and the results showed good quality.

• The Journal of the Korea Contents Association
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• v.7 no.2
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• pp.63-72
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• 2007

The traffic sign on the road should be easy to distinguishable even from far, and should be recognized in a short time. As traffic sign is a very important object which provides important information for the drivers to enhance safety, it has to attract human's attention among any other objects on the road. This paper proposes a new method of detecting the area of traffic sign, which uses attention module on the assumption that we attention our gaze on the traffic sign at first among other objects when we drive a car. In this paper, we analyze the previous studies of psycophysical and physiological results to get what kind of features are used in the process of human's object recognition, especially color processing, and with these results we detected the area of traffic sign. Various kinds of traffic sign images were tested, and the results showed good quality(average 97.8% success).

• Proceedings of the KSME Conference
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• 2002.08a
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• pp.729-732
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• 2002

This paper reports an experimental study around a module about forced air flow by blower($35{\times}35{\times}6mm^3$) in portable PC(10mm high, 200mm wide, and 235mm long). The channel inlet flow velocity has been varied between 0.26, 0.52 and 0.78m/s. The power input to the module is 4Wthis report, particular attention is directed to the fluid flow and adiabatic wall temperature($T_(ad)$) around a module which is under fluid mechanical and thermal influences of the module. The fluid flow around a module was visualized using PIV system. Liquid crystal thernography is used to determine the adiabatic wall temperature around a heated module on an acrylic board. Plots of $T_(ad)$ (or F) show marked effects of dispersion of thermal wake near the module.

• Journal of Information Processing Systems
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• v.18 no.4
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• pp.575-586
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• 2022

Uneven light in real-world causes visual degradation for underexposed regions. For these regions, insufficient consideration during enhancement procedure will result in over-/under-exposure, loss of details and color distortion. Confronting such challenges, an unsupervised low-light image enhancement network is proposed in this paper based on the guidance of the unpaired low-/normal-light images. The key components in our network include super-resolution module (SRM), a GAN-based low-light image enhancement network (LLIEN), and denoising-scaling module (DSM). The SRM improves the resolution of the low-light input images before illumination enhancement. Such design philosophy improves the effectiveness of texture details preservation by operating in high-resolution space. Subsequently, local lightness attention module in LLIEN effectively distinguishes unevenly illuminated areas and puts emphasis on low-light areas, ensuring the spatial consistency of illumination for locally underexposed images. Then, multiple discriminators, i.e., global discriminator, local region discriminator, and color discriminator performs assessment from different perspectives to avoid over-/under-exposure and color distortion, which guides the network to generate images that in line with human aesthetic perception. Finally, the DSM performs noise removal and obtains high-quality enhanced images. Both qualitative and quantitative experiments demonstrate that our approach achieves favorable results, which indicates its superior capacity on illumination and texture details restoration.

• Journal of the Korea Safety Management & Science
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• v.17 no.3
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• pp.371-375
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• 2015

Smartphone industry grew rapidly enough to draw a close attention in a short period less than ten years. Accordingly, required camera module industry is getting increase. In this study, it will be shown how to improve the productivity of new product model for the camera module before the growth to maximize the company profits.

• Smart Media Journal
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• v.13 no.3
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• pp.53-61
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• 2024

This paper presents a novel M-shaped encoder-decoder architecture for skin lesion segmentation, achieving better performance than existing approaches. The proposed architecture utilizes the left and right legs to enable multi-scale feature extraction and is further enhanced by integrating an attention module within the skip connection. The image is partitioned into four distinct patches, facilitating enhanced processing within the encoder-decoder framework. A pivotal aspect of the proposed method is to focus more on critical image features through an attention mechanism, leading to refined segmentation. Experimental results highlight the effectiveness of the proposed approach, demonstrating superior accuracy, precision, and Jaccard Index compared to existing methods

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.10
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• pp.2768-2787
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• 2023

As an important research direction of the application of computer science in the medical field, the automatic generation technology of radiology report has attracted wide attention in the academic community. Because the proportion of normal regions in radiology images is much larger than that of abnormal regions, words describing diseases are often masked by other words, resulting in significant feature loss during the calculation process, which affects the quality of generated reports. In addition, the huge difference between visual features and semantic features causes traditional multi-modal fusion method to fail to generate long narrative structures consisting of multiple sentences, which are required for medical reports. To address these challenges, we propose a multi-feature optimization Transformer (MFOT) for generating radiology reports. In detail, a multi-dimensional mapping attention (MDMA) module is designed to encode the visual grid features from different dimensions to reduce the loss of primary features in the encoding process; a feature pre-fusion (FP) module is constructed to enhance the interaction ability between multi-modal features, so as to generate a reasonably structured radiology report; a detail enhanced attention (DEA) module is proposed to enhance the extraction and utilization of key features and reduce the loss of key features. In conclusion, we evaluate the performance of our proposed model against prevailing mainstream models by utilizing widely-recognized radiology report datasets, namely IU X-Ray and MIMIC-CXR. The experimental outcomes demonstrate that our model achieves SOTA performance on both datasets, compared with the base model, the average improvement of six key indicators is 19.9% and 18.0% respectively. These findings substantiate the efficacy of our model in the domain of automated radiology report generation.

• 한국태양에너지학회:학술대회논문집
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• 2008.11a
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• pp.36-41
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• 2008

In this paper, we study The Effects of PV Cell's Electrical Characteristics for PV Module Application. Photovoltaic module consists of serially connected solar cell which has low open circuit voltage and high short circuit current characteristics. The whole current flow of PV module is restricted by lowest current of one solar cell. For the experiment, we make PV module composing the solar cells that have short circuit current difference of 0%, 1%, 3% and Random. The PV module exposed about 35days, its the maximum power drop ratio was 4.282% minimum and 6.657% maximum. And PV module of low current characteristics has electrical stress from other modules. The solar cell temperature of PV module was higher compared to PV cell. To prevent early degradation, it is need to have attention to PV cell selection.

• Journal of Information Processing Systems
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• v.19 no.1
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• pp.130-138
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• 2023

The traffic flow in an urban area is affected by the date, weather, and regional traffic flow. The existing methods are weak to model the dynamic road network features, which results in inadequate long-term prediction performance. To solve the problems regarding insufficient capacity for dynamic modeling of road network structures and insufficient mining of dynamic spatio-temporal features. In this study, we propose a novel traffic flow prediction framework called shared spatio-temporal attention convolution optimization network (SSTACON). The shared spatio-temporal attention convolution layer shares a spatio-temporal attention structure, that is designed to extract dynamic spatio-temporal features from historical traffic conditions. Subsequently, the graph optimization module is used to model the dynamic road network structure. The experimental evaluation conducted on two datasets shows that the proposed method outperforms state-of-the-art methods at all time intervals.

• The Journal of the Korea Contents Association
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• v.5 no.6
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• pp.87-96
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• 2005

In this paper, a selective visual attention module based on motion stimuli is introduced for the purpose of detecting ROI(region of interest) or FOA(focus of attention) in motion pictures. Analysis of motion fields in our approach is in direct contrast to some of the previous studies of selective visual attention module. Motion that presents temporal visual saliency in an aspect between two successive frames is analyzed based on psychological studies in 'DORF(double opponent receptive fields)' and 'NF(noise filtration)' in MT(middle temporal cortex). Analyzed results are integrated based on the theory of 'motion integration' in MT to obtain a single conspicuous region. Experiments through a human subjective evaluation showed generally accepted results.