Detecting Significant Events in Lecture Video using Supervised Machine Learning

被引：2

作者：

Brooks, Christopher ^{[1
]}

Amundson, Kristofor ^{[1
]}

Greer, Jim ^{[1
]}

机构：

[1] Univ Saskatchewan, Dept Comp Sci, Lab Adv Res Intelligent Educ Syst ARIES, Saskatoon, SK, Canada

来源：

ARTIFICIAL INTELLIGENCE IN EDUCATION: BUILDING LEARNING SYSTEMS THAT CARE: FROM KNOWLEDGE REPRESENTATION TO AFFECTIVE MODELLING | 2009年 / 200卷

关键词：

Course casting; video capture; supervised machine learning; significant events; chaptering; indexing; multimedia; HIGH AGREEMENT; LOW KAPPA;

D O I：

10.3233/978-1-60750-028-5-483

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper describes work we are doing to identify significant events in video captures of academic lectures. Unlike other approaches which tend to define per-image comparison threshold values based on intuition or empirically derived results, we use supervised machine teaming techniques to automatically determine appropriate image characteristics based on end-users understanding of what constitutes an important event. This makes our approach more adaptable to different kinds of content, and still provides a substantial level of agreement with human experts.

引用

页码：483 / +

页数：2

共 50 条

[1] Detecting Mislabeled Data Using Supervised Machine Learning Techniques
Poel, Mannes
[J]. AUGMENTED COGNITION: NEUROCOGNITION AND MACHINE LEARNING, AC 2017, PT I, 2017, 10284 : 571 - 581
[2] Detecting insurance fraud using supervised and unsupervised machine learning
Debener, Joern
Heinke, Volker
Kriebel, Johannes
[J]. JOURNAL OF RISK AND INSURANCE, 2023, 90 (03) : 743 - 768
[3] Detecting Cyberbullying in Social Commentary Using Supervised Machine Learning
Raza, Muhammad Owais
Memon, Mohsin
Bhatti, Sania
Bux, Rahim
[J]. ADVANCES IN INFORMATION AND COMMUNICATION, VOL 2, 2020, 1130 : 621 - 630
[4] Classification of Space Particle Events using Supervised Machine Learning Algorithms
Saric, Rijad
Chen, Junchao
Krstic, Milos
Custovic, Edhem
Panic, Goran
Kevric, Jasmin
Jokic, Dejan
[J]. 2021 IEEE 8TH INTERNATIONAL CONFERENCE ON DATA SCIENCE AND ADVANCED ANALYTICS (DSAA), 2021,
[5] Detecting Under-Resolved Flow Physics Using Supervised Machine Learning
Hedayat, Amirpasha
Ollivier-Gooch, Carl
[J]. AIAA JOURNAL, 2023, 61 (09) : 3958 - 3975
[6] In the Zone: Towards Detecting Student Zoning Out Using Supervised Machine Learning
Drummond, Joanna
Litman, Diane
[J]. INTELLIGENT TUTORING SYSTEMS, PART II, 2010, 6095 : 306 - 308
[7] DETECTING MALICIOUS PDF DOCUMENTS USING SEMI-SUPERVISED MACHINE LEARNING
Jiang, Jianguo
Song, Nan
Yu, Min
Chow, Kam-Pui
Li, Gang
Liu, Chao
Huang, Weiqing
[J]. ADVANCES IN DIGITAL FORENSICS XVII, 2021, 612 : 135 - 155
[8] Detecting Anomalous Behavior of PLC using Semi-supervised Machine Learning
Yau, Ken
Chow, K. P.
Yiu, S. M.
Chan, C. F.
[J]. 2017 IEEE CONFERENCE ON COMMUNICATIONS AND NETWORK SECURITY (CNS), 2017, : 580 - 585
[9] Detecting authorship deception: a supervised machine learning approach using author writeprints
Pearl, Lisa
Steyvers, Mark
[J]. LITERARY AND LINGUISTIC COMPUTING, 2012, 27 (02): : 183 - 196
[10] Detecting fake reviews with supervised machine learning algorithms
Lee, Minwoo
Song, Young Ho
Li, Lin
Lee, Kyung Young
Yang, Sung-Byung
[J]. SERVICE INDUSTRIES JOURNAL, 2022, 42 (13-14): : 1101 - 1121

← 1 2 3 4 5 →