CIES: Cloud-based Intelligent Evaluation Service for video homework using CNN-LSTM network

被引：7
作者：
Song, Rui [1 ]
Xiao, Zhiyi [2 ]
Lin, Jinjiao [1 ,3 ]
Liu, Ming [1 ,4 ]
机构：
[1] Shandong Univ, Sch Control Sci & Engn, Jinan 250002, Peoples R China
[2] Qingdao Univ Sci & Technol, Coll Electromech Engn, Qingdao 266061, Peoples R China
[3] Shandong Univ Finance & Econ, Sch Management Sci & Engn, Jinan 250014, Peoples R China
[4] Shandong Univ Sci & Technol, Coll Elect Engn & Automat, Jinan 250031, Peoples R China
来源：
JOURNAL OF CLOUD COMPUTING-ADVANCES SYSTEMS AND APPLICATIONS | 2020年 / 9卷 / 01期
关键词：
Video assignments; cloud computing; convolution neural networks; long short-term memory; intelligent evaluation; NEURAL-NETWORK;
D O I：
10.1186/s13677-020-0156-5
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Video (used as a form of examination or homework) as an efficient approach for examining students' abilities is drawing increasing attention in the education field. How to assess video assignments effectively and accurately has become a significant topic in academia. This work proposes a method based on a multi-channel CNN-LSTM hybrid architecture to extract and classify image features such as students' actions and expressions, as well as audio features such as speech rates and pauses in the video assignments, and then conducts a two-category assessment of "qualified" or "unqualified". Additionally, build this system in a cloud computing environment as a Cloud-based Intelligent Evaluation Service application could provide universal service to meet the needs of multiple teaching units. The proposed method is shown to be feasible and effective through experiments.
引用
收藏
页数：9
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