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- 8Artificial Intelligence
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- 4Convolutional Neural Networks
- 1Aghaei, Nikoo
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A Framework for Associating Mobile Devices to Individuals Based on Identification of Motion Events
DownloadFall 2020
The ubiquity of the Internet-of-Things (IoT) devices in everyday life allows various sensors to be utilized in networked systems for solving a number of real-world problems. Models utilizing specific sensing modalities achieve impressive performance in understanding human activity and are used in...
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Fall 2021
The management of project documentation involves processing a large amount of important information embedded in different contract and project specification documents. Although contract-related documentation is critical for effective information flow and—in turn—successful project management, it...
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Spring 2022
Data augmentation is a strong tool for enhancing the performance of deep learning models using different techniques to increase both the quantity and diversity of training data. Cutout was previously proposed, in the context of image classification, as a simple regularization technique that...
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Advancing Forest Health Monitoring: Harnessing the Power of Deep Learning Computer Vision for Remote Sensing Applications
DownloadFall 2023
Forests provide immense economic, ecological, and societal values, making forest health monitoring (FHM) a crucial task for guiding conservation and management of these essential ecosystems. Drones have seen increased popularity in this domain due to their ability to collect high-resolution,...
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An Exploration of Dialog Act Classification in Open-domain Conversational Agents and the Applicability of Text Data Augmentation
DownloadFall 2023
Recognizing dialog acts of users is an essential component in building successful conversational agents. In this work, we propose a dialog act (DA) classifier for two of our open domain conversational agents. For this, we curated a high-quality, multi-domain dataset with ∼24k user utterances...
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Spring 2023
3D reconstruction of quadruped animals is a challenging problem, where key issues lie in their large shape variety and deformation within the same animal species as well as the lack of sufficient training data. In this thesis, we present two approaches toward this task. Our first approach is a...
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Application of Natural Language Processing and Information Retrieval in Two Software Engineering Tools
DownloadFall 2021
Many software engineering problems have traditionally been approached by applying techniques based on static analysis and fixed sets of rules. I created two novel techniques to tackle three software engineering problems: typo location, fix suggestion, and crash report bucket creation. However,...
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Spring 2021
This thesis applies computer vision and machine learning techniques to three engineering projects: a self-driving vehicle, a predictive display system, and a vision-based robot manipulator joint detector. In the first project, we build a remote-controlled car and implement three core self-driving...
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Fall 2009
Answer typing is an important aspect of the question answering process. Most commonly addressed with the use of a fixed set of possible answer classes via question classification, answer typing influences which answers will ultimately be selected as correct. Answer typing introduces the concept...
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Spring 2023
Predicting a dense depth map from LiDAR scans and synced RGB images with a small deep neural network is a challenging task. Most top-accuracy methods boost precision by having a very large number of parameters and as a result huge memory consumption. Whereas, depth completion tasks are commonly...