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Skip to Search Results- 1Elkerdawy, Sara
- 1Foroughi, Homa
- 1Hajebi, Kiana
- 1Hosseinzadeh Heydarabad,Sepideh
- 1Liu, Yang
- 1Mills, Michael J
- 2SLAM
- 1Active contour model
- 1Adaptive multi-motion model
- 1Appearance-based SLAM
- 1Automated Vehicle
- 1Collective Perception
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Spring 2022
Automated Vehicle (AV) is a trending technology being developed with the promise to reduce traffic accidents caused by human errors. Perception plays a crucial role for Automated Driving Systems (ADS) to make safe decisions. However, local sensory data is insufficient to capture comprehensive...
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Spring 2017
At the core of many computer vision methods lies the question of how to represent data. Representing the data in a meaningful way, which highlights its most useful properties, can significantly affect the performance of any vision-based application. Traditional systems are heavily reliant on...
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Fall 2022
Deep neural networks (DNN) have emerged as the state-of-the-art method in several research areas. DNN is yet to fully permeate resource-constrained computing platforms, such as mobile phones. Accurate DNN models being deeper and wider take considerable memory and time to execute on small devices...
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Spring 2015
There is considerable research work going on segmentation of RGB-D clouds due its applications in tasks like scene understanding, robotics etc. The availability of inexpensive and easy to use RGB-D cameras and computational capabilities of GPUs has lead to development of numerous applications in...
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Spring 2018
Hosseinzadeh Heydarabad,Sepideh
In this work we address the problem of fast shadow detection from single images of natural scenes. Different from traditional methods that employ expensive optimization methods, we propose a fast semantic-aware Convolutional Neural Network learning framework which trains on different kinds of...
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Shape Based Joint Detection and Tracking with Adaptive Multi-motion Model and its Application in Large Lump Detection
DownloadSpring 2012
This thesis is motivated by a practical real application, Large Lump Detection (LLD), for which we provide a complete automatic system to detect large lumps in the oil sands mining surveillance videos. To this end, we propose a solution built around three main research components, each of which...
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Fall 2012
This dissertation contributes to developing shape-guided algorithms for interactive image segmentation. Prior knowledge which describes what is expected in an image is the key to success for many challenging applications. This research takes advantage of prior knowledge in terms of shape priors,...
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Fall 2014
This thesis is concerned with the ultrasonic heart image segmentation problem using parametric active contour model. Most of the existing parametric models consider only either the edge or the regional information. In this thesis, we propose a new parametric active contour model considering both...