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Clinical and Translational Biophotonics, Translational 2022

作者： Tweel, James Pellegrino, Nicholas Ecclestone, Benjamin R. Fieguth, Paul Reza, Parsin Haji PhotoMedicine Labs Systems Design Engineering University of Waterloo WaterlooONN2L 3G1 Canada Vision and Image Processing Lab Systems Design Engineering University of Waterloo WaterlooONN2L 3G1 Canada Illumisonics Inc. 22 King Street South WaterlooONN2J 1N8 Canada

Characteristic time-domain (TD) features are extracted from Photoacoustic Remote Sensing TD modulation using a novel temporal clustering algorithm. Features correspond to tissue-specific structures in unprocessed rese... 详细信息

ISBN: (纸本)9781557528209

关键词： Tissue

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Image registration using virtual circles and edge direction

Image registration using virtual circles and edge direction

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16th International Conference on Pattern Recognition, ICPR 2002

作者： Alhichri, Haikel Salem Kamel, Mohamed Systems Design Engineering Pattern Analysis and Machine Intelligence Lab University of Waterloo WaterlooONN2L3G1 Canada

ISBN: (纸本)0769516963

In this paper, we combine a novel set of image features called virtual circles with edge direction, to provide an efficient alignment algorithm for image registration under similarity transformations. Virtual circles can be extracted efficiently from many types of images with the kelp of the distance transform. They can also have extra information, such as their radius and the dominant edge direction in neighborhood, which can be used for efficient registration. A heuristic called the smoothness criterion is used to choose virtual circles which are less likely to be corrupted by background noise, and to increases the efficiency of the algorithm. Experimental results have shown that this method is highly automatic and has linear complexity in terms of the number of virtual circles extracted. © 2002 IEEE.

关键词： Image registration

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A reinfrocement learning approach to online learning in control

A reinfrocement learning approach to online learning in cont...

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Fourth International Conference on Control and Automation

作者： Tehrani, Ali M. Kamel, Mohamed S. Pattern Analysis and Machine Intelligence Lab Systems Design Engineering Department University of Waterloo Waterloo Ont. N2L 3G1 Canada

ISBN: (纸本)078037777X

In search for a reinforcement learning technique with the simplicity of tabular techniques and capability of dealing with continuous states like in fuzzy systems, we introduce a new approach, which we have called Adaptive Pseudo Fuzzy technique. The idea is to partition the state space with some window functions similar to fuzzy membership functions and learn the output values by changing the rules' consequents directly. This is a kind of local function approximation similar to RBFs and CMACs , however, unlike RBFs it does not shift the basis, and unlike CMACs it does not go through complex coarse coding. This method represents the input as a fuzzy system and learns the output as a look-up-table. We employed this technique in Sarsa(λ) to build a general online controller and examined it for a pole-balancing problem. © 2003 IEEE.

关键词： Learning systems

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CMNN: Cooperative Modular Neural Network

CMNN: Cooperative Modular Neural Network

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1997 IEEE International Conference on Neural Networks (ICNN 97)

作者： Auda, G Kamel, M Pattern Analysis and Machine Intelhgence Lab Systems Design Engineering Department University of Waterloo N2L 3G1 Canada

ISBN: (纸本)0780341236

The current generation of non-modular neural network classifiers is unable to cope with classification problems which have a wide range of overlap among classes. This is due to the high coupling among the networks' hidden nodes. We propose the Cooperative Modular Neural Network (CMNN) architecture, which deals with different levels of overlap in different modules. The modules share their information and cooperate in taking a global classification decision through voting. Moreover, special modules are dedicated to resolve high overlaps in the input-space. The performance of the new model outperforms that of the nonmodular alternative when when applied to ten famous benchmark classification problems.

关键词： Neural networks

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Multi-scale saliency-guided compressive sensing approach to efficient robotic laser range measurements

Multi-scale saliency-guided compressive sensing approach to ...

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2012 9th Conference on Computer and Robot Vision, CRV 2012

作者： Schwartz, Shimon Wong, Alexander Clausi, David A. Department of Systems Design Engineering University of Waterloo Vision and Image Processing Lab. Research Group Waterloo ON N2L 3G1 Canada

ISBN: (纸本)9780769546834

Improving laser range data acquisition speed is important for many robotic applications such as mapping and localization. One approach to reducing acquisition time is to acquire laser range data through a dynamically small subset of measurement locations. The reconstruction can then be performed based on the concept of compressed sensing (CS), where a sparse signal representation allows for signal reconstruction at sub-Nyquist measurements. Motivated by this, a novel multi-scale saliency-guided CS-based algorithm is proposed for an efficient robotic laser range data acquisition for robotic vision. The proposed system samples the objects of interest through an optimized probability density function derived based on multi-scale saliency rather than the uniform random distribution used in traditional CS systems. Experimental results with laser range data from indoor and outdoor environments show that the proposed approach requires less than half the samples needed by existing CS-based approaches while maintaining the same reconstruction performance. In addition, the proposed method offers significant improvement in reconstruction SNR compared to current CS-based approaches. © 2012 IEEE.

关键词： Compressed sensing

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Surface ghosts: Promoting awareness of transferred objects during pick-and-drop transfer in multi-surface environments 14

Surface ghosts: Promoting awareness of transferred objects d...

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9th ACM International Conference on Interactive Tabletops and Surfaces, ITS 2014

作者： Scott, Stacey D. Besacier, Guillaume Tournet, Julie Goyal, Nippun Haller, Michael Systems Design Engineering University of Waterloo WaterlooON Canada Games Institute University of Waterloo WaterlooON Canada Université Paris 8 Saint-Denis France Télécom Bretagne Brest France Media Interaction Lab University of Applied Sciences Upper Austria Hagenberg Austria

ISBN: (纸本)9781450325875

Rekimoto's Pick-and-Drop (P&D) transfer technique is commonly used to support multi-surface object transfer (e.g., between a shared tabletop and tablet) due to its easily understood metaphor of emulating object movement in the physical world. Current multi-surface implementations of P&D provide little to no feedback during transfer, causing confusion for the person performing the action as well as others in the environment. To address this issue, we investigated the use of virtual embodiments to improve awareness of transferred objects, in the context of a real-world group task that relied heavily on cross-device transfer. An iterative design process led to the design of Surface Ghosts virtual embodiments, which take the form of semitransparent "ghosts" of the transferred objects displayed under the "owner's" hand on the tabletop during transfer. A user study that compared two Surface Ghosts designs- varied by how explicitly the "owner" was indicated- showed that both designs improved awareness of transferred objects when compared to a no-feedback control condition, especially for tabletop-to-tablet transfers. Copyright © 2014 ACM.

关键词： Drops

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Application of an enhanced deep super-resolution network in retinal image analysis 30

Application of an enhanced deep super-resolution network in ...

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30th Conference on Ophthalmic Technologies

作者： Gulati, Tanmay Sengupta, Sourya Lakshminarayanan, Vasudevan Department of Computer Science and Engineering Manipal Institute of Technology Manipal India Theoretical and Experimental Epistemology Lab School of Optometry and Vision Science University of Waterloo ON Canada Department of Systems Design Engineering University of Waterloo ON Canada

ISBN: (纸本)9781510631991

Fundus imaging is widely used for the diagnosis of retinal diseases. Major ophthalmic diseases like glaucoma, diabetic retinopathy (DR), age-related macular degeneration (AMD) are diagnosed by examining retinal fundus images. Therefore, the efficient and reliable diagnosis largely depends upon the resolution of the images. In different diseased conditions, different pathologies and landmarks (haemorrhages, microaneurysms, exudates, blood vessels, optic disc and optic cup, fovea) of the retina get affected. In clinical situations it is often not possible to obtain good high-resolution images. Here, the techniques of super-resolution can be applied. The objective of super-resolution is to obtain a high-resolution image from a low-resolution input image. In this paper, we present results of the application of enhanced deep residual networks for single image super-resolution (EDSR) on retinal fundus images. This network is based on the SRResNet architecture involving skip connections. Using the public RIGA dataset, which consists of glaucoma and normal fundus images, we have trained the model using 2x, 4x and 8x scaling with three different optimizers each (namely ADAM, Stochastic Gradient Descent and RMSprop) to determine which optimizer is best for the different scales. We have also provided results obtained by varying the residual blocks in the network. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Diagnosis

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Image registration using collinear virtual circles

Image registration using collinear virtual circles

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Proceedings: 2003 International Conference on Image Processing, ICIP-2003

作者： Alhichri, Haikel Salem Kamel, Mohamed Pattern Anal./Mach. Intelligence Lab Systems Design Engineering University of Waterloo Waterloo Ont. N2L 3G1 Canada

In this paper, we present an improved image registration algorithm based on the virtual circles features. Virtual circles are extracted efficiently by finding the local maxima in the distance transform of the edge maps. Virtual circles are grouped into collinear set to which a line is fitted to determine the direction. The radii of the virtual circles in the group as well as the direction of the fitted line are used in the registration algorithm. The Hausdorff fraction is also used as a similarity measure to determine the optimal transformation. This algorithm can find large translation, rotation, and scale differences between two images. Further more, it has linear complexity in terms of the number of virtual circles extracted.

关键词： Image analysis

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Control Task Analysis in Action: Collaboration in the Operating Room

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Proceedings of the Human Factors and Ergonomics Society Annual Meeting 2011年第1期55卷 272 - 276页

作者： Maryam Ashoori Catherine Burns Kathryn Momtahan Barbara d’Entremont Advanced Interface Design Lab University of Waterloo Nursing Professional Practice Department The Ottawa Hospital

Cognitive Work Analysis (CWA) is gaining momentum for analyzing complex socio-technical systems but it does not yet have the specific tools and techniques that allow it to address teamwork explicitly enough to provide good guidance on how to support teams. This paper focuses on expansion of control task analysis (ConTA), the second phase of CWA, to understand the collaborative decision making of a surgical team during Cesarean section surgery.

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Data dependence in combining classifiers

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4th International Workshop on Multiple Classifier systems, MCS 2003

作者： Kamel, Mohamed S. Wanas, Nayer M. Pattern Analysis and Machine Intelligence lab Department of Systems Design Engineering University of Waterloo WaterlooONN2L-3G1 Canada

ISBN: (纸本)3540403698

It has been accepted that multiple classifier systems provide a platform for not only performance improvement, but more efficient and robust pattern classification systems. A variety of combining methods have been proposed in the literature and some work has focused on comparing and categorizing these approaches. In this paper we present a new categorization of these combining schemes based on their dependence on the data patterns being classified. Combining methods can be totally independent from the data, or they can be implicitly or explicitly dependent on the data. It is argued that data dependent, and especially explicitly data dependent, approaches represent the highest potential for improved performance. On the basis of this categorization, an architecture for explicit data dependent combining methods is discussed. Experimental results to illustrate the comparative performance of some combining methods according to this categorization is included. © Springer-Verlag Berlin Heidelberg 2003.

关键词： Computers

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