• Title/Summary/Keyword: 파이토치

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CNN model transition learning comparative analysis based on deep learning for image classification (이미지 분류를 위한 딥러닝 기반 CNN모델 전이 학습 비교 분석)

  • Lee, Dong-jun;Jeon, Seung-Je;Lee, DongHwi
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.370-373
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    • 2022
  • Recently, various deep learning framework models such as Tensorflow, Pytorch, Keras, etc. have appeared. In addition, CNN (Convolutional Neural Network) is applied to image recognition using frameworks such as Tensorflow, Pytorch, and Keras, and the optimization model in image classification is mainly used. In this paper, based on the results of training the CNN model with the Paitotchi and tensor flow frameworks most often used in the field of deep learning image recognition, the two frameworks are compared and analyzed for image analysis. Derived an optimized framework.

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Framework Switching of Speaker Overlap Detection System (화자 겹침 검출 시스템의 프레임워크 전환 연구)

  • Kim, Hoinam;Park, Jisu;Cha, Shin;Son, Kyung A;Yun, Young-Sun;Park, Jeon Gue
    • Journal of Software Assessment and Valuation
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    • v.17 no.1
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    • pp.101-113
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    • 2021
  • In this paper, we introduce a speaker overlap system and look at the process of converting the existed system on the specific framework of artificial intelligence. Speaker overlap is when two or more speakers speak at the same time during a conversation, and can lead to performance degradation in the fields of speech recognition or speaker recognition, and a lot of research is being conducted because it can prevent performance degradation. Recently, as application of artificial intelligence is increasing, there is a demand for switching between artificial intelligence frameworks. However, when switching frameworks, performance degradation is observed due to the unique characteristics of each framework, making it difficult to switch frameworks. In this paper, the process of converting the speaker overlap detection system based on the Keras framework to the pytorch-based system is explained and considers components. As a result of the framework switching, the pytorch-based system showed better performance than the existing Keras-based speaker overlap detection system, so it can be said that it is valuable as a fundamental study on systematic framework conversion.

Image Classification of Endangered Species of Migratory Birds Using Pytorch (Pytorch를 통한 멸종위기종 철새 이미지 분류 AI 시스템)

  • Chae-Young Shim;Joon-Woo Lee;Min-Jung Choo;Da-Hui Hwang;Yoo-Jin Moon
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2023.01a
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    • pp.319-320
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    • 2023
  • 본 논문에서는 합성곱 신경망이 적용된 네트워크를 활용해 전이 학습의 과정을 거친 멸종위기종 철새들의 이미지를 분류하는 시스템의 설계과정과 결과를 제시한다. 연구 방법으로 한국 영랑호를 찾아오는 멸종위기종, 천연기념물인 철새들의 이미지를 학습시켜 "가창오리", "노랑부리백로", "물총새" 이 세 종의 철새들을 매우 정확하게 분류하는 것을 확인하였다. 데이터 예비학습과정에서 train data의 개수를 40개로 진행했을때 약 92%의 정확도를 확인 후, train data의 이미지 개수를 50장으로 늘려 더 높은 정확도를 얻을 수 있었다. 이 시스템은 한국을 방문하는 멸종위기종 철새들을 무분별하게 포획하지 않도록 철새 이미지 분류시 활용 가능하다고 사료된다.

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Security Vulnerability Verification for Open Deep Learning Libraries (공개 딥러닝 라이브러리에 대한 보안 취약성 검증)

  • Jeong, JaeHan;Shon, Taeshik
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.29 no.1
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    • pp.117-125
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    • 2019
  • Deep Learning, which is being used in various fields recently, is being threatened with Adversarial Attack. In this paper, we experimentally verify that the classification accuracy is lowered by adversarial samples generated by malicious attackers in image classification models. We used MNIST dataset and measured the detection accuracy by injecting adversarial samples into the Autoencoder classification model and the CNN (Convolution neural network) classification model, which are created using the Tensorflow library and the Pytorch library. Adversarial samples were generated by transforming MNIST test dataset with JSMA(Jacobian-based Saliency Map Attack) and FGSM(Fast Gradient Sign Method). When injected into the classification model, detection accuracy decreased by at least 21.82% up to 39.08%.

Analysis of Mediating Effects of Eating Habits on the Relationship between Stress and Depression in the Elderly (노인의 스트레스와 우울 간의 관계에서 식습관의 매개 효과 분석)

  • Tak, Sang Sook;Lee, Geo Lyong
    • Journal of Naturopathy
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    • v.11 no.2
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    • pp.93-99
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    • 2022
  • Background: It is necessary to understand the correlation between stress and depression according to eating habits in the elderly. Purposes: To empirically verify the mediating effect of eating habits in the relationship between stress and depression in the elderly. Methods: we distributed an 'online questionnaire' to men and women aged 60 or more living in large cities, medium, and small-sized cities in Korea using Google questionnaires, and 365 replies were collected and used for analysis. Results: First, we found that stress in the elderly directly affected depression. In summary, an increment in the stress level of the elderly induces an increment in the depression level. Second, the eating habits of the elderly indirectly mediated the relationship between stress and depression. Conclusions: This study is meaningful in that it has verified eating habits have a mediating effect on the relationship between stress and depression in the elderly, and healthy eating habits of individuals can reduce depression. Therefore, counseling institution must check their daily eating habits when counseling the degree of depression of the elderly. In addition, eating habits are affected by stress, and it is necessary to grasp the individual stress index for the elderly who has terrible eating habits. Furthermore, it is needed to provide continuous nutrition education in institutions and communities to have proper eating habits.