OrigamiSet1.0: Two New Datasets for Origami Classification and Difficulty Estimation
원문 초록
Origami is becoming more and more relevant to research. However, there is no public dataset yet available and there hasn't been any research on this topic in machine learning. We constructed an origami dataset using images from the multimedia commons and other databases. It consists of two subsets: one for classification of origami images and the other for difficulty estimation. We obtained 16000 images for classification (half origami, half other objects) and 1509 for difficulty estimation with $3$ different categories (easy: 764, intermediate: 427, complex: 318). The data can be downloaded at: https://github.com/multimedia-berkeley/OriSet. Finally, we provide machine learning baselines.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
ExploreKit: Automatic Feature Generation and Selection
Thumbs up? Sentiment Classification using Machine Learning Techniques
Semantic Structure Enhanced Contrastive Adversarial Hash Network for Cross-media Representation Learning
Analysis of Kepler Objects of Interest using Machine Learning for Exoplanet Identification
Twitter Sentiment Analysis
Generative Adversarial Minority Oversampling for Spectral-Spatial Hyperspectral Image Classification
토론
이 논문과 연결된 포럼 글이 아직 없습니다.