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Seasonal Images Classification with Convolutional Neural Networks
Aaron Daniel Snowberger(에런 스노버거),Choong Ho Lee(이충호) 한국정보통신학회 2022 한국정보통신학회 종합학술대회 논문집 Vol.26 No.1
최근 몇 년 동안 더 깊은 신경망 아키텍처로 인해 컴퓨터 비전 이미지 분류 작업이 더 빠르고 더 좋아졌다. 그러나 대부분의 이미지 분류 작업은 특정 이미지 모양(예: 고양이와 개 구별)을 기반으로 분류 하도록 설계되었지만 낮과 밤 또는 사계절과 같은 기간을 구별하도록 훈련된 분류 모델은 많지 않다. 같은 장소의 사계절 이미지를 구분하기 위한 선행 연구는 있는 반면 일반 영상의 계절 분류 연구는 현재 부재한 실정이다. 그래서 본 논문에서는 일반 영상의 계절 분류 문제에 대한 다양한 접근 방식을 제시한다. 간단한 특징 추출부터 합성곱 신경망 구축, 전이 학습에 이르기까지 계절별 이미지 분류를 위한 세 가지 방법을 연구하고 정확도 결과를 비교, 분석하였다. In recent years, computer vision image classification tasks have become faster and better due to deeper neural network architectures. But while most image classification tasks are designed to classify images based on specific image features (such as distinguishing between cats and dogs), there are not many classification models that have been trained to distinguish between time periods such as day and night or different seasons of the year. And while some research has been done into distinguishing between seasons in images of the same location, this paper presents a varied approach to the problem of seasonal classification of generic images. Three methods for seasonal image classification, from simple feature extraction, to building a convolutional neural network, to transfer learning were studied and the accuracy results were compared and analyzed.
Handwritten Hangul Graphemes Classification Using Three Artificial Neural Networks
Aaron Daniel Snowberger,Choong Ho Lee The Korea Institute of Information and Commucation 2023 Journal of information and communication convergen Vol.21 No.2
Hangul is unique compared to other Asian languages because of its simple letter forms that combine to create syllabic shapes. There are 24 basic letters that can be combined to form 27 additional complex letters. This produces 51 graphemes. Hangul optical character recognition has been a research topic for some time; however, handwritten Hangul recognition continues to be challenging owing to the various writing styles, slants, and cursive-like nature of the handwriting. In this study, a dataset containing thousands of samples of 51 Hangul graphemes was gathered from 110 freshmen university students to create a robust dataset with high variance for training an artificial neural network. The collected dataset included 2200 samples for each consonant grapheme and 1100 samples for each vowel grapheme. The dataset was normalized to the MNIST digits dataset, trained in three neural networks, and the obtained results were compared.
Aaron Daniel Snowberger,Choong Ho Lee 한국정보통신학회 2021 한국정보통신학회 종합학술대회 논문집 Vol.25 No.2
In 2021, Tokyo held the delayed 2020 Olympics in the ongoing COVID-19 pandemic. As with any Olympics, the final medal count was of particular interest. Since 2004. South Korea has consistently ranked in the top ten most successful countries for four straight Summer Olympics. However, in 2021, it fell short of a top ten finish for the first time since 2004. There may be many factors that affect the final medal count in any Olympics, and this study compares and looks for correlations between some of these factors including final medal count, GDP, population, size of Olympic contingent, and Freedom Index. The study pays particular attention to South Korea and other countries which have seen a dramatic change in Freedom Index score since 1972. when the index was first published.
Manchu Script Letters Dataset Creation and Labeling
Aaron Daniel Snowberger,Choong Ho Lee 한국정보통신학회JICCE 2024 Journal of information and communication convergen Vol.22 No.1
The Manchu language holds historical significance, but a complete dataset of Manchu script letters for training optical character recognition machine-learning models is currently unavailable. Therefore, this paper describes the process of creating a robust dataset of extracted Manchu script letters. Rather than performing automatic letter segmentation based on whitespace or the thickness of the central word stem, an image of the Manchu script was manually inspected, and one copy of the desired letter was selected as a region of interest. This selected region of interest was used as a template to match all other occurrences of the same letter within the Manchu script image. Although the dataset in this study contained only 4,000 images of five Manchu script letters, these letters were collected from twenty-eight writing styles. A full dataset of Manchu letters is expected to be obtained through this process. The collected dataset was normalized and trained using a simple convolutional neural network to verify its effectiveness.
스노우버거 다니엘 아론(Aaron Daniel Snowberger),이충호(Choong Ho Lee) 한국정보통신학회 2021 한국정보통신학회 종합학술대회 논문집 Vol.25 No.2
청나라 황제가 신하들과 정사를 논한 내용을 기록한 중국의 어문청정은, 한국의 조선실록과 같은 중요한 문서이다. 본 논문은 만주글자로 쓰여진 어문청정을 빅데이터 분석하기 위한 방법과 그 단계를 기술한다. 만주글자로 씌여진 문서의 빅데이터 분석에는 사전에 해결해야 할 많은 문제가 있으며 이에 대한 연구가 선행되어야 한다. 본 논문에서는 앞으로 이루어질 사전 연구를 통하여 만주 글자로 씌여진 텍스트가 라틴문자로 전사된 단계에서, R언어를 이용하여 빅데이터 분석을 하는 방법을 제안하였다. 제안된 방법에서는 어문청정을 전사하는 방식은 압카이 방식을 채택하였고, 위문기거 부분의 텍스트를 이용하여 빅데이터 분석 결과를 제시하였다. Yumentingzheng, which records the contents of the Qing dynasty’s discussions with his subjects, is an important document like the Annals of Joseon in Korea. This paper describes the method and steps for big data analysis of Yumentingzheng written in Manchu alphabet. In big data analysis of documents written in Manchu characters, there are many problems that need to be solved in advance, and research on these should be preceded. In this paper, a method of big data analysis using the R language was proposed in the stage where the text written in Manchurian characters was transliterated into Latin characters through a preliminary study to be conducted in the future. In the proposed method, Apkai method was adopted for the transliteration of Wumentingzheng, and the results of big data analysis were presented using the text of Weiwenqiju.
스노우버거 아론 다니엘(Aaron Daniel Snowberger),이충호(Choong Ho Lee) 한국정보통신학회 2021 한국정보통신학회 종합학술대회 논문집 Vol.25 No.1
만주 문자는 세로로 쓰여지며 한 단어 안에서는 띄어쓰기 없이 이어져 있기 때문에 문자를 인식하기 전에 글자영역 분리와 글자를 이루는 단위를 분리해 내는 전처리과정이 필요하다. 본 논문에서는 글자영역을 추출하고 글자의 단위를 끊어내는 전처리 방법을 기술한다. 기존 연구가 단어별 또는 문자단위로 인식하는 방법을 전제로 하거나, 이어져 있는 글자의 줄기를 없앤 후 남는 부분으로 인식하는 것과 달리, 본 방법은 인식 가능한 단위별로 글자를 끊어낸 다음 그 단위의 합성으로 글자를 인식하는 방법에 적용할 수 있다. 실험을 통하여 본 방법의 유효성을 검증하였다. Since Manchu characters are written vertically and are connected without spaces within a word, a preprocessing process is required to separate the character area and the units that make up the characters before recognizing the characters. In this paper, we describe a preprocessing method that extracts the character area and cuts off the unit of the character. Unlike existing research that presupposes a method of recognizing each word or character unit, or recognizing the remaining part after removing the stem of a continuous character, this method cuts the character into each recognizable unit. It can be applied to the method of recognizing letters by combining the units. Through an experiment, the effectiveness of this method was verified.