arXiv:1304.6933
Digit Recognition in Handwritten Weather Records
원문 초록
This paper addresses the automatic recognition of handwritten temperature values in weather records. The localization of table cells is based on line detection using projection profiles. Further, a stroke-preserving line removal method which is based on gradient images is proposed. The presented digit recognition utilizes features which are extracted using a set of filters and a Support Vector Machine classifier. It was evaluated on the MNIST and the USPS dataset and our own database with about 17,000 RGB digit images. An accuracy of 99.36% per digit is achieved for the entire system using a set of 84 weather records.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
LINEA: Fast and Accurate Line Detection Using Scalable Transformers
BST: Badminton Stroke-type Transformer for Skeleton-based Action Recognition in Racket Sports
The Impact of Semi-Supervised Learning on Line Segment Detection
CmdCaliper: A Semantic-Aware Command-Line Embedding Model and Dataset for Security Research
Enhancing Soccer Camera Calibration Through Keypoint Exploitation
SegHist: A General Segmentation-based Framework for Chinese Historical Document Text Line Detection
토론
이 논문과 연결된 포럼 글이 아직 없습니다.