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Cover Song Identification - A Novel Stem-Based Approach To Improve Song-To-Song Similarity Measurements, Lavonnia Newman, Dhyan Shah, Chandler Vaughn, Faizan Javed
Cover Song Identification - A Novel Stem-Based Approach To Improve Song-To-Song Similarity Measurements, Lavonnia Newman, Dhyan Shah, Chandler Vaughn, Faizan Javed
SMU Data Science Review
Music is incorporated into our daily lives whether intentional or unintentional. It evokes responses and behavior so much so there is an entire study dedicated to the psychology of music. Music creates the mood for dancing, exercising, creative thought or even relaxation. It is a powerful tool that can be used in various venues and through advertisements to influence and guide human reactions. Music is also often "borrowed" in the industry today. The practices of sampling and remixing music in the digital age have made cover song identification an active area of research. While most of this research is focused …
Cognition And Context-Aware Computing: Towards A Situation-Aware System With A Case Study In Aviation, Justin C. Wilson
Cognition And Context-Aware Computing: Towards A Situation-Aware System With A Case Study In Aviation, Justin C. Wilson
Computer Science and Engineering Theses and Dissertations
In aviation, flight instructors seek to comprehend the intent and awareness of their students. With this awareness, derived from in-flight observation and post-flight examination, a human instructor can infer the internal contexts of their student aviators as they perform. It is this understanding that is fundamental for evaluating student development. Further, a well-understood construct for describing the state of knowledge about a dynamic environment is known as situational awareness (SA). Often pilot error is associated with SA [80], and it is fundamental to flight safety and mission execution. If these contexts can be automatically inferred, instructors and students can more …
A Modeling Framework For Urban Growth Prediction Using Remote Sensing And Video Prediction Technologies: A Time-Dependent Convolutional Encoder-Decoder Architecture, Ahmed Hassan Jaad
A Modeling Framework For Urban Growth Prediction Using Remote Sensing And Video Prediction Technologies: A Time-Dependent Convolutional Encoder-Decoder Architecture, Ahmed Hassan Jaad
Civil and Environmental Engineering Theses and Dissertations
Studying the growth pattern of cities/urban areas has received considerable attention during the past few decades. The goal is to identify directions and locations of potential growth, assess infrastructure and public service requirements, and ensure the integration of the new developments with the existing city structure. This dissertation presents a novel model for urban growth prediction using a novel machine learning model. The model treats successive historical satellite images of the urban area under consideration as a video for which future frames are predicted. A time-dependent convolutional encoder-decoder architecture is adopted. The model considers as an input a satellite image …
Improving Syntactic Relationships Between Language And Objects, Benjamin Wilke, Tej Tenmattam, Anand Rajan, Andrew Pollock, Joel Lindsey
Improving Syntactic Relationships Between Language And Objects, Benjamin Wilke, Tej Tenmattam, Anand Rajan, Andrew Pollock, Joel Lindsey
SMU Data Science Review
This paper presents the integration of natural language processing and computer vision to improve the syntax of the language generated when describing objects in images. The goal was to not only understand the objects in an image, but the interactions and activities occurring between the objects. We implemented a multi-modal neural network combining convolutional and recurrent neural network architectures to create a model that can maximize the likelihood of word combinations given a training image. The outcome was an image captioning model that leveraged transfer learning techniques for architecture components. Our novelty was to quantify the effectiveness of transfer learning …