METHOD FOR TRAINING A MODEL TO IDENTIFY HULL BLOCKS BASED ON A CONVOLUTIONAL NEURAL NETWORK
The present invention relates to a hull block identification model learning method based on a convolutional neural network (CNN) which models and learns a plurality of images obtained by rotating a hull block object in 3D CAD data by multi-views based on a CNN, thereby automatically identifying and...
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| Format: | Patent |
| Sprache: | eng ; kor |
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| Zusammenfassung: | The present invention relates to a hull block identification model learning method based on a convolutional neural network (CNN) which models and learns a plurality of images obtained by rotating a hull block object in 3D CAD data by multi-views based on a CNN, thereby automatically identifying and classifying a hull block from data obtained from a camera.
본 발명은 3차원 캐드(CAD) 데이터 내 선체 블록 객체를 다시점으로 회전시켜 획득되는 다수의 영상을 합성곱신경망(CNN)에 기반하여 모델링 및 학습시킴으로써, 카메라로부터 획득되는 데이터로부터 선체 블럭을 자동으로 식별, 분류 할 수 있도록 하는 합성곱신경망에 기반한 선체 블록 식별 모델 학습 방법에 관한 것이다. |
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