• IEIE Transactions on Smart Processing and Computing
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• v.5 no.1
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• pp.49-54
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• 2016

Regarding global and local factors of a set of features, a given single image or multiple images is a common approach in image processing. This paper introduces an application of an adaptive version of non-local filter whose original version searches non-local similarity for removing noise. Since most images involve texture partner in both foreground and background, extraction of signified regions with texture is a challenging task. Aiming to the detection of visual attention regions for images with texture, we present the contrast analysis of image patches located in a whole image but not nearby with assistance of the adaptive filter for estimation of non-local divergence. The method allows extraction of signified regions with texture of images of wild life. Experimental results for a benchmark demonstrate the ability of the proposed method to deal with the mentioned challenge.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.16 no.1
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• pp.33-46
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• 2005

First, the author reviewed the relationship between human brain development and cognitive functions such as attention, perception, memory, and language. And then Luria's neurodevelopmental theory and its application on the Neuropsychological test battery for children were reviewed. Finally, various assessment tools to evaluate attention, intellectual function, visual-perception, visual-motor coordination, and executive function were examined.

• Journal of Sensor Science and Technology
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• v.13 no.2
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• pp.144-151
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• 2004

In this paper, we propose an active stereo surveillance system with human-like convergence function. The proposed system uses a bottom-up saliency map model with the human-like selective attention visual function to select an interesting region in each camera. and this system compares the landmarks whether the selective region in each camera finds a same region. If the left and right cameras successfully find a same landmarks, the implemented vision system focuses on the landmark. Using the motor encoder information, we can automatically obtain the depth information and resultantly construct a depth map using the depth information. Computer simulation and experimental results show that the proposed convergence method is very effective to implement the active stereo surveillance system.

• Fashion & Textile Research Journal
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• v.3 no.3
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• pp.204-210
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• 2001

The purpose of the study is to clarify red image in the modem fashion. 40 kinds of costume samples being visual power in red have been selected from photographs in fashion magazines and divided into tones: pale (Vp, Lgr, L), bright (P, B), vivid (S, B, Dp), dark (Gr, Dl, Dgr, Dk). The study was measured by using Semantic Differential method. The subjects were 50 students majoring in clothing and textile. The data were analyzed by factor analysis, ANOVA, discrimminant analysis, MDS and regression analysis. The results of analysis are as follow; 1. Factor analysis has extracted 5 factors of red image in the fashion. These factor are Attractiveness, Hardness and Softness, Emotion, Attention, Simplicity. 2. There were significant difference in visual evaluation of red tones. 3. The discrimination among 4 red tones was related to attention and weight of red. 4. Evaluative dimensions of red was classified as Soft-Hard, Lively-Decent. 5. The image effect on Preference, Buying needs, Pleasant and Riches was consist of complicated sensibility.

• Journal of the Korea Computer Graphics Society
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• v.13 no.3
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• pp.1-6
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• 2007

Anticipation effect has been used as a traditional skill to enhance the dynamic motion of the traditional 2D animation. Basically, anticipation means the action of opposite direction which performs before the real action step. In this paper, we propose the perception-based video anticipation method to guide a user's visual attention to the important region. Using the image based attention map, we calculate the visual attention region and then combine this map with temporal saliency of video. We apply the anticipation effect in these saliency regions using the blur kernel. Using our method, we can generate the dynamic video motion which has attentive guidance.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.26 no.1
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• pp.45-51
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• 2015

Objectives : Children with attention-deficit hyperactivity disorder (ADHD) have been shown to display more inhibitory deficits and executive function deficits. This study investigated the treatment effects of neurofeedback (NF) training on executive function by comparing the results of neuropsychological tests of the trained children at pre- and post-training. Methods : Fifteen children with ADHD, aged 6 to 14 years, participated in the study. The NF treatment consisted of slow cortical potential (SCP) training and these sessions took place once a week. The ADHD children performed 20 sessions of NF training within 6 months. Pre-training and post-training assessments encompassed Continuous Performance Test (CPT), Stroop Test, Children's Color Trails Test I&II (CCTT) and Wisconsin Card Sorting Test (WCST). Results : Patients receiving NF training showed significant improvement in visual commission error and standard deviation of auditory response time on CPT ; and total errors on WCST. But there was no significant improvement in the Stroop test and CCTT. Conclusion : SCP training using NF improves the self-regulatory capacities and impulsivity in ADHD patient, especially impulsivity in visual stimulation tasks. This study showed evidence of clinical efficacy of NF on executive function in ADHD.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.4
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• pp.145-151
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• 2021

In this paper, we propose a novel visualization technique to explain the predictions of deep neural networks. We use knowledge distillation (KD) to identify the interior of a black-box model for which we know only inputs and outputs. The information of the black box model will be transferred to a white box model that we aim to create through the KD. The white box model will learn the representation of the black-box model. Second, the white-box model generates attention maps for each of its layers using Grad-CAM. Then we combine the attention maps of different layers using the pixel-wise summation to generate a final saliency map that contains information from all layers of the model. The experiments show that the proposed technique found important layers and explained which part of the input is important. Saliency maps generated by the proposed technique performed better than those of Grad-CAM in deletion game.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.851-853
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• 2022

고령화로 인해 65세 이상 운전자가 급증하며 고령운전자의 교통사고 비율이 증가함에 따라 시급한 사회 문제로 떠오르고 있다. 이에 본 연구에서는 객체 검출, 인식 모델을 결합하고 신호등을 인식하여 Text-To-Speech(TTS)로 알리는 쿠버네티스 기반의 프레임워크를 제안한다. 객체 검출 단계에서는 YOLOv5 모델들의 성능을 비교하여 활용하였으며 객체 인식 단계에서는 C-RNN 기반의 attention-OCR 모델을 활용하였다. 이는 신호등의 내부 LED 영역이 아닌 이미지 전체를 인식하는 방식으로 오탐지 요소를 낮춰 인식률을 높였다. 결과적으로 1,628장의 테스트 데이터에서 accuracy 0.997, F1-score 0.991의 성능 평가를 얻어 제안한 프레임워크의 타당성을 입증하였다. 본 연구는 후속 연구에서 특정 도메인에 딥러닝 모델을 한정하지 않고 다양한 분야의 모델을 접목할 수 있도록 하며 고령 운전자 및 신호 위반으로 인한 교통사고 문제를 예방할 수 있다.

• ETRI Journal
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• v.33 no.4
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• pp.600-610
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• 2011

This paper presents a novel approach to face detection by localizing faces as the goal-specific saliencies in a scene, using the framework of selective visual attention of a human with a particular goal in mind. The proposed approach aims at achieving human-like robustness as well as efficiency in face detection under large scene variations. The key is to establish how the specific knowledge relevant to the goal interacts with the bottom-up process of external visual stimuli for saliency detection. We propose a direct incorporation of the goal-related knowledge into the specification and/or modification of the internal process of a general bottom-up saliency detection framework. More specifically, prior knowledge of the human face, such as its size, skin color, and shape, is directly set to the window size and color signature for computing the center of difference, as well as to modify the importance weight, as a means of transforming into a goal-specific saliency detection. The experimental evaluation shows that the proposed method reaches a detection rate of 93.4% with a false positive rate of 7.1%, indicating the robustness against a wide variation of scale and rotation.

• Korean Journal of Cognitive Science
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• v.16 no.1
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• pp.1-15
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• 2005

Since human visual system has limited capacity for visual information processing, it should select goal-relevant information for further processing. There have been several studies that emphasized the possible involvement of memory in spatial shift of selective attention (Chun & Jiang, 1998, 1999; Klein, 1988; Klein & MacInnes, 1999). However, other studies suggested the inferiority of human visual memory in change detection(Rensink, O'Regan, & Clark, 1997; Simons & Levin, 1997) and in visual search(Hotowitz & Wolfe, 1998). The present study examined the involvement of memory in visual search; whether memory for the previously searched items guides selective attentional shift or not. We investigated how search works by comparing visual search performances in three different conditions; full exposure condition, partial exposure condition, and partial-to-full exposure condition. Revisiting searched items was allowed only in full exposure condition and not in either partial or partial-to-full exposure condition. The results showed that the efficiencies of attentional shift were nearly identical for all conditions. This finding implies that even in full exposure condition the participants scarcely re-examined the previously searched items. The results suggest that instant memory can be formed and used in visual search process. These results disagree with the earlier studies claiming thar visual search has no memory. We discussed the problems of the previous research paradigms and suggested some alternative accounts.