CCKS2019中文命名实体识别任务。从医疗文本中识别疾病和诊断、解剖部位、影像检查、实验室检验、手术和药物6种命名实体。现已实现基于jieba和AC自动机的baseline构建、基于BiLSTM和CRF的序列标住模型构建。bert的部分代码主要源于https://github.com/charles9n/bert-sklearn.git 感谢作者。 模型最终测试集得分0.81,还有较大改进空间。可以当做一个baseline。
CTPN + DenseNet + CTC based end-to-end Chinese OCR implemented using tensorflow and keras
FreeSWITCH is a Software Defined Telecom Stack enabling the digital transformation from proprietary telecom switches to a versatile software implementation that runs on any commodity hardware. From a Raspberry PI to a multi-core server, FreeSWITCH can unlock the telecommunications potential of any device.
gunicorn 'Green Unicorn' is a WSGI HTTP Server for UNIX, fast clients and sleepy applications.
A Neural Grapheme-to-Phoneme Conversion Package for Mandarin Chinese Based on a New Open Benchmark Dataset
Plumb a PDF for detailed information about each char, rectangle, line, et cetera — and easily extract text and tables.