• Proceedings of the Korea Multimedia Society Conference
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• 2002.11b
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• pp.93-96
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• 2002

불연속선에 의해 생성된 기하학적 착시에서 특징 점들을 추출하는 시각 모델을 제안한다. 기하학적 착시는 선이나 원으로 구성된 것으로서 인간의 정보처리 경로를 통해 발생하는 인지현상중의 하나이다. 이러한 인지 현상은 외부 세계에 존재하는 동일한 강도의 물리적 에너지를 주변자극의 영향 때문에 실제와 다르게 해석하는 현상이다. 착시 그림들로부터 착시 윤곽을 이루는 특징 점을 추출하는 시각 모델을 제안한다. 제안된 인식 모델은 윤곽 추출, 시각 특징 추출, 시각특징 복원, 유도 자극 추출, 이미지 복원 및 이미지 연산 단계로 구성된다. 제안된 모델은 불연속적인 선에 의해 나타나는 착시 윤곽에서 특징 자극들을 추출한다.

• Korean Journal of Cognitive Science
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• v.22 no.4
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• pp.347-364
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• 2011

In this paper, we propose a automatic image bases extraction method for visual image reconstruction from brain activity using Non-negative Matrix Factorization (NMF). Image bases are basic elements to construct and present a visual image. Previous method used brain activity that evoked by predefined 361 image bases of four different sizes: $1{\times}1$, $2{\times}1$, $1{\times}2$, $2{\times}2$, and $2{\times}2$. Then the visual stimuli were reconstructed by linear combination of all the results from these image bases. While the previous method used 361 predefined image bases, the proposed method automatically extracts image bases which represent the image data efficiently. From the experiments, we found that the proposed method reconstructs the visual stimuli better than the previous method.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.11a
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• pp.683-686
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• 2002

본 연구는 불연속선에 의해 생성된 시각적 착시에서 착시 윤곽의 특징들을 구하는 인식 모델을 제안한다. 착시 윤곽은 일상생환에서 흔히 접하는 현상으로서 외부 세계에 존재하는 동일한 강도의 물리적 에너지를 주변 자극의 영향 때문에 실제와 다르게 해석하는 현상이다. 착시 그림들로부터 착시 윤곽을 이루는 특징 자극을 추출하는 신경회로망 모델을 제안한다. 제안된 인식 모델은 윤곽 추출, 시파 특징 추출, 시파 특징 복원, 유도 자극 추출, 이미지 복원 및 이미지 연산 단계로 구성된다. 제안된 모델은 불연속적인 선에 의해 나타나는 오프셋 격자 윤곽에서 특징 자극들을 추출한다.

• Journal of Biomedical Engineering Research
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• v.38 no.6
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• pp.342-351
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• 2017

The neural decoding is a procedure that uses spike trains fired by neurons to estimate features of original stimulus. This is a fundamental step for understanding how neurons talk each other and, ultimately, how brains manage information. In this paper, the strategies of neural decoding are classified into three methodologies: rate decoding, temporal decoding, and population decoding, which are explained. Rate decoding is the firstly used and simplest decoding method in which the stimulus is reconstructed from the numbers of the spike at given time (e. g. spike rates). Since spike number is a discrete number, the spike rate itself is often not continuous and quantized, therefore if the stimulus is not static and simple, rate decoding may not provide good estimation for stimulus. Temporal decoding is the decoding method in which stimulus is reconstructed from the timing information when the spike fires. It can be useful even for rapidly changing stimulus, and our sensory system is believed to have temporal rather than rate decoding strategy. Since the use of large numbers of neurons is one of the operating principles of most nervous systems, population decoding has advantages such as reduction of uncertainty due to neuronal variability and the ability to represent a stimulus attributes simultaneously. Here, in this paper, three different decoding methods are introduced, how the information theory can be used in the neural decoding area is also given, and at the last machinelearning based algorithms for neural decoding are introduced.

• Korean Journal of Ecology and Environment
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• v.56 no.4
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• pp.406-413
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• 2023

Captive breeding and reintroduction are crucial strategies for conserving endangered species populations. However, fish raised in predator-free environments, show a lack of recognition of predationrelated stimuli such as chemical and visual signals. It is critical to recognize chemical signals from injured conspecifics, also known as alarm signals, and the order or shape of predators to indicate the spread of predation risk in the habitat. We conducted a laboratory experiment to determine and adjust the optimal exposure period to induce appropriate anti-predator behavior response to different types of stimuli (Chemical, Visual and Chemical+Visual) for the endangered species Microphysogobio rapidus. Our results demonstrate that predator avoidance behavior varies depending on the types of stimuli and the duration of predation risk exposure. First, the results showed captive-breed M. rapidus show lack of response against conspecific alarm signal (Chemical cue) before the predation risk exposure period and tend to increase response over predation risk exposure time. Second, response to predator (visual cue) tend to peak at 48 hours cumulative exposure, but show dramatic decrease after 72 hours cumulative exposure. Finally, response to the mixed cue (Chemical+visual) tend to peak prior to the predation risk exposure period and show reduced response during subsequent exposure periods. This experiment confirms the lack of responsiveness to conspecific alarm signals in captive-bred M. rapidus and the need for an optimal nature behavior enhancement program prior to release of endangered species. Furthermore, responsiveness to predator visual signal peak at 48 hours cumulative exposure, suggest an optimal predation risk exposure period of up to 48 hours.