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Skip to Search Results- 144Machine Learning
- 23Depression
- 19Artificial Intelligence
- 17Reinforcement Learning
- 15Deep Learning
- 10Computer Vision
- 2Wen, Junfeng
- 1Aghaei, Nikoo
- 1Aghamohammadi Sereshki, Arash
- 1Al Dallal, Ahmed
- 1Al-Masri, Mohammad
- 1Alam Anik, Md Tanvir
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Fall 2019
Dialogue systems, also known as Conversational Agent (CA), are designed to mimic coherent conversations with humans. Most conversational agents are specialized for a specific domain such as travel booking and are typically finite state-based or template-based. Open domain dialogue systems have...
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Spring 2023
Traditional survey based methods for clinical depression detection are not always effective; the patient may not reflect their actual mental health condition because of the cognitive bias exhibited while filling out questionnaires about depression. Established through ample earlier work, social...
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Fall 2018
Information extraction (IE) is one of the most important technologies in the information age. Applying information extraction to text is linked to the prob- lem of text simplification in order to create a structured view of the informa- tion present in free text. However, information extraction...
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Fall 2023
The increasing popularity of Deep Neural Networks (DNN) has led to their application to many domains, including Music Generation. However, these large DNN-based models are heavily dependent on their training dataset, which means they perform poorly on musical genres that are out-of-distribution...
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Spring 2016
Depression is a common, recurrent and frequently chronic mental health disorder that has already become one of the leading health-care burdens. Despite the wide clinical application of antidepressants, a significant portion of patients does not benefit sufficiently from the standard medication...
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Fall 2019
This thesis aims to develop a motion control strategy for an Unmanned Aerial Vehicle (UAV) to execute a pursuit algorithm based on a vision based object detection algorithm. This enables a pursuer UAV to follow a target UAV based on images obtained from the onboard camera of the pursuer. The UAV...
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Fall 2020
This thesis is offered as a step forward in our understanding of forgetting in artificial neural networks. ANNs are a learning system loosely based on our understanding of the brain and are responsible for recent breakthroughs in artificial intelligence. However, they have been reported to be...
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Fall 2022
Sentence reconstruction and generation are essential applications in Natural Language Processing (NLP). Early studies were based on classic methods such as production rules and statistical models. Recently, the prevailing models typically use deep neural networks. In this study, we utilize deep...
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Spring 2020
Reinforcement learning (RL) is a powerful learning paradigm in which agents can learn to maximize sparse and delayed reward signals. Although RL has had many impressive successes in complex domains, learning can take hours, days, or even years of training data. A major challenge of contemporary...
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Fall 2023
Giving reasons for justifying the decisions made by classification models has received less attention in recent artificial intelligence breakthroughs than improving the accuracy of the models. Recently, AI researchers are paying more attention to filling this gap, leading to the introduction of...