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Now showing items 31-40 of 65
Lightweight deep learning for monocular depth estimation
(2021)
Monocular depth estimation is a challenging but significant part of computer
vision with many applications in other areas of study. This estimation method aims to
provide a relative depth prediction for a single input ...
Surface estimation from multi-modal tactile data
(2021)
The increasing popularity of Robotic applications has seen use in healthcare, surgery,
and as an industrial tool. These robots are expected to be able to make physical
contact with the objects in the environment which ...
Semi-supervised framework for clustering and semantic segmentation
(2021)
During the past couple of decades, machine learning and deep learning methods have
achieved remarkable results in many real-world applications. However, it is difficult
to develop and train these artificial intelligence ...
Congestion control enhancement over wireless networks
(2019)
In this thesis, we analyze the performance of wireless LAN networks subject to random loss. In this regard, we use a congestion control technique that has been introduced in a previous study, titled TCP Congestion Control ...
Data-driven traversability estimation for mobile robot navigation
(2021)
Mobile robots have a promising application prospect as they can assist or replace
humans to perform laborious, repetitive or dangerous tasks in various scenarios. There
has been a large number of studies for mobile robot ...
3D GPU-based image reconstruction algorithm for the application in a clinical organ-targeted PET camera
(2022)
Functional medical imaging is unique in its ability to visualize molecular interactions and
pathways in the body. Organ-targeted Positron Emission Tomography (PET) is a
functional imaging technique that has emerged to ...
Multi-timeframe algorithmic trading bots using thick data heuristics with deep reinforcement learning
(2022)
This thesis presents an augmented Artificial Intelligence (AI) algorithmic trading
approach that combines Thick Data Heuristics (TDH), with Deep Reinforcement Learning
(DRL), to successfully learn trading execution timing ...
Federated learning framework and energy disaggregation techniques for residential energy management
(2023)
Residential energy use is a significant part of total power usage in developed countries. To reduce overall
energy use and save funds, these countries need solutions that help them keep track of how different
appliances ...
Exploration of contrastive learning strategies toward more robust stance detection systems
(2023)
Stance Detection, in general, is the task of identifying the author’s position on controversial topics. In Natural Language Processing, Stance Detection extracts the
author’s attitude from the text written toward an issue ...
Detecting Crohn’s disease from high resolution endoscopy videos: the thick data approach
(2023)
Detecting diseases in high resolution endoscopy videos can be done in several ways
depending on the methodology for detection. One such method that has been a hot topic
in the field of medical technology research is the ...