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Full-Text Articles in Physical Sciences and Mathematics
Video Game Genre Classification Based On Deep Learning, Yuhang Jiang
Video Game Genre Classification Based On Deep Learning, Yuhang Jiang
Masters Theses & Specialist Projects
Video games have played a more and more important role in our life. While the genre classification is a deeply explored research subject by leveraging the strength of deep learning, the automatic video game genre classification has drawn little attention in academia. In this study, we compiled a large dataset of 50,000 video games, consisting of the video game covers, game descriptions and the genre information. We explored three approaches for genre classification using deep learning techniques. First, we developed five image-based models utilizing pre-trained computer vision models such as MobileNet, ResNet50 and Inception, based on the game covers. Second, …
Book Genre Classification By Its Cover Using A Multi-View Learning Approach, Chandra Shakhar Kundu
Book Genre Classification By Its Cover Using A Multi-View Learning Approach, Chandra Shakhar Kundu
Masters Theses & Specialist Projects
An interesting topic in the visual analysis is to determine the genre of a book by its cover. The book cover is the very first communication to the reader which shapes the reader’s expectation about the type of the book. Each book cover is carefully designed by the cover designers and typographers to convey the visual representation of its content. In this study, we explore several different deep learning approaches for predicting the genre from the cover image alone, such as MobileNet V1, MobileNet V2, ResNet50, Inception V2. Moreover, we add an extra modality by extracting text from the cover …
A Description Of A Humans Knowledge Using Artificial Intelligence, Dj Price
A Description Of A Humans Knowledge Using Artificial Intelligence, Dj Price
Mahurin Honors College Capstone Experience/Thesis Projects
There currently does not exist a way to easily view the relationships between a collection of written items (e.g. sports articles, diary entries, research papers). In recent years, novel machine learning methods have been developed which are very good at extracting semantic relationships from large numbers of documents. One of them is the (unsupervised) machine learning model Doc2Vec which constructs vectors for documents. The research project detailed in this paper uses this and other already existing algorithms to analyze the relationship between pieces of text. We set forth a broader ambition for this project before discussing the use and need …