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Skip to Search Results- 8Deep Learning
- 2Anomaly Detection
- 2Machine Learning
- 2Recommender Systems
- 1 Fuzzy Logic
- 1Alarm Filter
- 1Akbari, Mojtaba
- 1Amini, Iman
- 1Dolatabadi, Amirhossein
- 1Gong, Xiaohui
- 1Han, Xuefei
- 1Mehrabi, Mehrtash
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Fall 2022
With the rapid development of smart grids, the detection of anomalies is essential to improve the quality and security protection of the grid. The identification of anomalies not only saves valuable time but also reduces maintenance costs. Due to the increasing deployment of distributed energy...
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Spring 2021
Deep learning has revolutionized many fields that process large amounts of data such as images, video, audio, speech, and text. Anomaly detection, however, is among the areas that still require major advancements. Based on the key traits of deep learning, which are the need for very little hand...
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Data-Driven Based Methods for Physical Layer Detection and Estimation in 5G and Beyond Wireless Communication Systems
DownloadFall 2023
The fifth-generation (5G) mobile network is growing rapidly and is set to revolutionize the way we communicate, work and live. It offers faster speeds, lower latency, and greater capacity than previous generations of mobile networks. Three main use cases have been defined for fifth-generation...
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Spring 2021
Nowadays, leakage detection is of great importance as pipelines are the major means of transporting hydrocarbon fluids and gases. In this thesis, we propose two methods based on supervised learning and filtering to deal with the pipeline leakage detection problem. First, a novel two-stage...
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Deep Learning-based Forecasting and Energy Management Algorithms for Smart Grid Applications
DownloadFall 2023
With the increasing global problems concerning energy security and climate change, new challenges in social progress and human survival have come to the fore. Requiring no fuel, and being renewable and non-polluting, renewable energy (RE) resources, typically from photovoltaic and wind sources,...
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Fall 2019
Search query understanding is a trending topic in the field of Information Retrieval (IR). The goal is to learn higher-level representations for the intents or concepts behind a search query and utilize these representations to further enhance down-stream services like content recommendation....
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Spring 2019
While deep learning has proven to be a powerful new tool for modeling and predicting a wide variety of complex phenomena, those models remain incomprehensible black boxes. This is a critical impediment to the widespread deployment of deep learning technology, as decades of research have found...
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Motion Planning of Robotic Systems in Diagnostic and Therapy Applications Using Control and AI
DownloadFall 2023
This thesis presents significant research on robotic motion planning within diagnostic and therapy applications, with a primary focus on the integration of control and AI techniques. The research encompasses three main contributions: a robotic ultrasound imaging method, a robot-assisted...
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Fall 2017
With the proliferation of e-commerce business, the study of online user purchasing behavior plays an important role in improving purchasing experiences of users as well as providing valuable intelligence to sellers. While most previous research efforts focused on explicit user behavior modeling,...
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Fall 2017
Recommender systems are a modern solution for suggesting new items to users. One of their uses is for novel point of interest recommendation, recommending locations to a user which they have not visited. This can be applied to a location-based social network, which contains information about...