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Full-Text Articles in Physical Sciences and Mathematics
Design And Implementation Of A Domain Specific Language For Deep Learning, Xiao Bing Huang
Design And Implementation Of A Domain Specific Language For Deep Learning, Xiao Bing Huang
Theses and Dissertations
\textit {Deep Learning} (DL) has found great success in well-diversified areas such as machine vision, speech recognition, big data analysis, and multimedia understanding recently. However, the existing state-of-the-art DL frameworks, e.g. Caffe2, Theano, TensorFlow, MxNet, Torch7, and CNTK, are programming libraries with fixed user interfaces, internal representations, and execution environments. Modifying the code of DL layers or data structure is very challenging without in-depth understanding of the underlying implementation. The optimization of the code and execution in these tools is often limited and relies on the specific DL computation graph manipulation and scheduling that lack systematic and universal strategies. Furthermore, …
Speech Emotion Recognition Using Convolutional Neural Networks, Somayeh Shahsavarani
Speech Emotion Recognition Using Convolutional Neural Networks, Somayeh Shahsavarani
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
Automatic speech recognition is an active field of study in artificial intelligence and machine learning whose aim is to generate machines that communicate with people via speech. Speech is an information-rich signal that contains paralinguistic information as well as linguistic information. Emotion is one key instance of paralinguistic information that is, in part, conveyed by speech. Developing machines that understand paralinguistic information, such as emotion, facilitates the human-machine communication as it makes the communication more clear and natural. In the current study, the efficacy of convolutional neural networks in recognition of speech emotions has been investigated. Wide-band spectrograms of the …
Quantitative Behavior Tracking Of Xenopus Laevis Tadpoles For Neurobiology Research, Alexander Hansen Hamme
Quantitative Behavior Tracking Of Xenopus Laevis Tadpoles For Neurobiology Research, Alexander Hansen Hamme
Senior Projects Fall 2018
Xenopus laevis tadpoles are a useful animal model for neurobiology research because they provide a means to study the development of the brain in a species that is both physiologically well-understood and logistically easy to maintain in the laboratory. For behavioral studies, however, their individual and social swimming patterns represent a largely untapped trove of data, due to the lack of a computational tool that can accurately track multiple tadpoles at once in video feeds. This paper presents a system that was developed to accomplish this task, which can reliably track up to six tadpoles in a controlled environment, thereby …