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Social and Behavioral Sciences Commons™
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Science and Technology Studies
Faculty of Applied Science and Technology - Exceptional Student Work, Applied Computing Theses
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- Alexnet (1)
- Automated continuity analysis (1)
- Automatic generated summaries (1)
- Automatic text summary (1)
- Autonomous vehicle (1)
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- Continuity editing (1)
- ConvNet model (1)
- Convolutional neural network (1)
- Coreferent resolution (1)
- Driverless vehicle (1)
- Generated summaries (1)
- Named entity recognition (1)
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- Robot vehicle (1)
- Self-driving (1)
- Statistic based summary (1)
- Subject identification techniques (1)
- Summarization techniques (1)
- Syntactic patterns (1)
- Unsupervised learning summarization (1)
Articles 1 - 3 of 3
Full-Text Articles in Social and Behavioral Sciences
Automatic Description: A Novel Approach To Documenting Character Description For Consistency In Long – Form Prose, Samantha Akulick
Automatic Description: A Novel Approach To Documenting Character Description For Consistency In Long – Form Prose, Samantha Akulick
Faculty of Applied Science and Technology - Exceptional Student Work, Applied Computing Theses
Currently, continuity editing for narrative fiction is performed manually. Many hours of human effort are required to comb through written works for inconsistencies. This study investigates the use of syntactic patterns of descriptions in narrative text and subject identification techniques like named entity recognition (NER) and coreferent resolution in narrative text as a step toward automated continuity analysis. This investigation involved examining natural English language to identify patterns used in descriptions and using natural language processing (NLP) techniques to identify those patterns and sentence subjects programmatically. Results were assessed by using the content of well-known works of fiction and two …
Detection Of Distracted Pedestrians Using Convolutional Neural Networks, Igor Grishchenko
Detection Of Distracted Pedestrians Using Convolutional Neural Networks, Igor Grishchenko
Faculty of Applied Science and Technology - Exceptional Student Work, Applied Computing Theses
The risk of pedestrian accidents has increased due to the distracted walking increase. The research in the autonomous vehicles industry aims to minimize this risk by enhancing the route planning to produce safer routes. Detecting distracted pedestrians plays a significant role in identifying safer routes and hence decreases pedestrian accident risk. Thus, this research aims to investigate how to use the convolutional neural networks for building an algorithm that significantly improves the accuracy of detecting distracted pedestrians based on gathered cues. Particularly, this research involves the analysis of pedestrian’ images to identify distracted pedestrians who are not paying attention when …
Automatic Extraction Of Useful Information From Food -Health Articles Related To Diabetes, Cardiovascular Disease And Cancer, Ken Sunong
Faculty of Applied Science and Technology - Exceptional Student Work, Applied Computing Theses
Food-health articles (FHA) contain invaluable information for health promotion. However, extracting this information manually is a challenging process due to the length and number of articles published yearly. Automatic text summarization efficiently identifies useful information across large bodies of text which in turn speeds up the delivery of useful information from FHA. This research work aims to investigate the performance of statistical based summarization and graphical based unsupervised learning summarization in extracting useful information from FHA related to diabetes, cardiovascular disease and cancer. Various combinations of introduction, result and conclusion sections of three hundred articles were collected, preprocessed and used …