지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2020.9
- 수록면
- 1,155 - 1,163 (9page)
이용수
초록· 키워드
오류제보하기
Deep learning approach is emerging as a new way to improve the accuracy of tree species identification using bark image. However, the approach has not been studied enough because it is confronted with the problem of acquiring a large volume of bark image dataset. This study solved this problem by utilizing a pretrained off-the-shelf DCNN model. It compares the discrimination power of bark features extracted by each DCNN model. Then it extracts the features by using a selected DCNN model and feeds them to a multi-layer perceptron (MLP). We found out that the ResNet50 model is effective in extracting bark features and the MLP could be trained well with the features reduced by the principal component analysis. The proposed approach gives accuracy of 99.1% and 98.4% for BarkTex and Trunk12 datasets respectively.
목차
ABSTRACT
1. 서론
2. DCNN 모델
3. 수피의 특징 추출 및 수종 인식
4. 실험 결과 및 분석
5. 결론
REFERENCE
참고문헌 (22)
참고문헌 신청
J. Waldchen and P. Mader, “Plant Species Identification Using Computer Vision Techniques: A Systematic Literature Review,” Archives of Computational Methods in Engineering, Vol. 25, No. 1, pp. 507-543, 2018.
R. Ratajczak, S. Bertrand, C.C. Junior, and L. Tougne, “Efficient Bark Recognition in the Wild,” Proceedings of the International Conference on Computer Vision Theory and Applications, pp. 240-248, 2019.
A. He and X. Tian, “Multi-organ Plant Identification with Multi-column Deep Convolutional Neural Networks,” Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, pp. 20-25, 2016.
Y. Zhao, X. Gao, J. Hu, Z. Chen, Z. Chen, and Z. Chen, “Tree Species Identification Based on the Fusion of Bark and Leaves,” Mathematical Biosciences and Engineering, Vol. 17, No. 4, pp. 4018-4033, 2020.
L.J. Blaanco, C.M. Traviesco, J.M. Quinteiro, P.V. Hernandez, M.K. Dutta, and A. Singh, “A Bark Recognition Algorithm for Plant Classification Using a Least Square Support Vector Machine,” Proceedings of the International Conference on Contemporary Computing, pp. 1-5, 2016.
R. Ratajczak, S. Bertrand, C.C. Junior, and L. Tougne, “Efficient Bark Recognition in the Wild,” Proceedings of the International Conference on Computer Vision Theory and Applications, pp. 240-248, 2019.
A. He and X. Tian, “Multi-organ Plant Identification with Multi-column Deep Convolutional Neural Networks,” Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, pp. 20-25, 2016.
Y. Zhao, X. Gao, J. Hu, Z. Chen, Z. Chen, and Z. Chen, “Tree Species Identification Based on the Fusion of Bark and Leaves,” Mathematical Biosciences and Engineering, Vol. 17, No. 4, pp. 4018-4033, 2020.
L.J. Blaanco, C.M. Traviesco, J.M. Quinteiro, P.V. Hernandez, M.K. Dutta, and A. Singh, “A Bark Recognition Algorithm for Plant Classification Using a Least Square Support Vector Machine,” Proceedings of the International Conference on Contemporary Computing, pp. 1-5, 2016.
함께 읽어보면 좋을 논문
논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!
-
보행 종류 분류를 위한 판별 거리 기반의 DCNN 특징 맵 구성 방법
한국정보과학회 학술발표논문집
2019 .06
-
DCNN 기반 콘크리트 성능평가 모델 개발 및 기대효과
건설관리 : 한국건설관리학회 학회지
2017 .01
-
Streamlining Computational Complexity: A Novel Data Processing Approach for Enhanced 3DCNN Performance in Human Action Recognition
한국정보과학회 학술발표논문집
2024 .06
-
Deep Convolutional Neural Network (DCNN) 기반의 단백질 간 상호 작용 추출
한국정보과학회 학술발표논문집
2016 .06
-
HLS 기법을 사용한 병렬 계층 기반 DCNN 가속기의 구현
Proceedings of KIIT Conference
2019 .11
-
Animal Face Classification using Dual Deep Convolutional Neural Network
멀티미디어학회논문지
2020 .04
-
비디오 얼굴 식별 성능개선을 위한 다중 심층합성곱신경망 결합 구조 개발
멀티미디어학회논문지
2019 .06
-
스마트 깔창의 센서를 이용한 보행 타입 분류 방법
한국통신학회논문지
2018 .08
-
객체 이미지를 이용한 객체간 관계 기반의 내용기반 이미지 검색 기법
한국정보기술학회논문지
2023 .01
-
이미지 내 객체 분류를 위한 노드 가지치기 기반 압축된 심층 합성곱 신경망 모델
디지털콘텐츠학회논문지
2022 .04
-
Deep Convolution Neural Networks in Computer Vision : a Review
IEIE Transactions on Smart Processing & Computing
2015 .02
-
A Recommendation Model based on Character-level Deep Convolution Neural Network
한국정보통신학회논문지
2019 .03
-
텍스처 특징 기반 제어점 선택 알고리즘과 병렬 심층 컨볼루션 신경망을 이용한 새로운 얼굴 모핑 방법
멀티미디어학회논문지
2022 .02
-
Anthropomorphic Animal Face Masking using Deep Convolutional Neural Network based Animal Face Classification
멀티미디어학회논문지
2019 .05
-
심층 신경망 기반의 앙상블 방식을 이용한 토마토 작물의 질병 식별
멀티미디어학회논문지
2020 .10
-
DeepMedNet: Deep Learning based Medical Image Segmentation Model
한국정보과학회 학술발표논문집
2021 .06
-
Person identification by using ResNet on hand images
제어로봇시스템학회 국제학술대회 논문집
2024 .10
-
Development of Real-Time Visibility Estimation from Camera Imagery using Dilated Convolutional Neural Networks
한국정보과학회 학술발표논문집
2019 .06
-
Toward Optimal FPGA Implementation of Deep Convolutional Neural Networks for Handwritten Hangul Character Recognition
Journal of Computing Science and Engineering
2018 .03
-
Classification of Osteoporosis from Phalanges CR Images Based on DCNN
제어로봇시스템학회 국제학술대회 논문집
2017 .10
이 논문의 저자 정보
최근 본 자료
댓글(0)
0