Other

Fudan University

Bgi Shenzhen

Huawei Technologies Co., Limited

Xiaoqing Liu

Dong Chen

Qian Wang

Yong Liu

Lei Wang

Jin Li

Wei He

Shuangshuang Li

Xun Xu

Wei Wang

Di Li

Lili Wang

Wenbin Chen

Heng Liu

Jun Wang

Zhihua Zhang

Huiwen Deng

Xisheng Tian

Shilong Wen

Yanhua Zhao

Haonan Wang

Hanwen Liu

Leilei Zhu

Yuxuan Liu

Liai Xu

Huayong Lu

Weixiang Ding

Shiqing Qian

Guowei Xu

Buyue Zhang

Ruiqi Xu

Lijia Tian

Jingyi Cheng

Jiaxu Hong

Yong Ni

Youwen Guo

A construction building equipment includes hanging pedestals, sleeve frames, hydraulic cylinders, upper reversing boxes, lower reversing boxes and track columns. The multiple hanging pedestals are fixed on an outer side of a shear wall of an external wall. The sleeve frames and the track columns are clamped on the hanging pedestals. The sleeve frames are clamped on outer sides of the track columns. The lower reversing boxes are fixed at upper ends of the sleeve frames. The hydraulic cylinders are connected with the upper reversing boxes and the lower reversing boxes. Side surfaces of the track columns are provided with pane holes for cooperative climbing of the upper reversing boxes and the lower reversing boxes. Upper ends of the track columns are fixedly connected with a top platform. Hangers and formworks are suspended on the top platform through booms.

Construction building equipment and construction method thereof

The present disclosure proposes a modeling method and apparatus for diagnosing an ophthalmic disease based on artificial intelligence, and a storage medium. The modeling method includes: establishing a data collection of ophthalmic images and a data collection of non-image ophthalmic disease diagnosis questionnaires; training a first neural network model by employing the data collection of the ophthalmic images to obtain a first classification model; training a second classification model by employing the data collection of non-image ophthalmic disease diagnosis questionnaires; and merging the first classification model and the second classification model to obtain a target classification network model, in which, a test result outputted by the target classification network model is used as a diagnosis result of the ophthalmic disease.

Modeling method and apparatus for diagnosing ophthalmic disease based on artificial intelligence, and storage medium

Growing community of inventors

Shenzhen, China

Xiaoqing Liu