T. Fevens

发表

Application of Pattern Recognition Techniques for the Analysis of Histopathological Images

Adam Krzyzak, Thomas Fevens, Lukasz Jelen, 2011, Computer Recognition Systems 4.

Discriminatory Power of Cells Grouping Features for Breast Cancer Malignancy Classification

A. Krzyżak, T. Fevens, Lukasz Jelen, 2008 .

One-Class Classification Decomposition for Imbalanced Classification of Breast Cancer Malignancy Data

Adam Krzyzak, Bartosz Krawczyk, Thomas Fevens, 2014, ICAISC.

White Blood Cell Differential Counts Using Convolutional Neural Networks for Low Resolution Images

A. Krzyżak, T. Fevens, Mehdi Habibzadeh, 2013, ICAISC.

Simple polygons with an infinite sequence of deflations.

Michael A. Soss, G. Toussaint, T. Fevens, 2001 .

Analysis of White Blood Cell Differential Counts Using Dual-Tree Complex Wavelet Transform and Support Vector Machine Classifier

Adam Krzyzak, Thomas Fevens, Mehdi Habibzadeh, 2012, ICCVG.

Energy Efficient Stable Routing Using Adjustable Transmission Ranges in Mobile Ad Hoc Networks

Thomas Fevens, Abedalmotaleb Zadin, T. Fevens, 2014, ADHOC-NOW.

Environment Lighting for Point Sampled Geometry

Feng Liu, Sudhir P. Mudur, Sushil Bhakar, 2006, International Conference on Computer Graphics, Imaging and Visualisation (CGIV'06).

Dual Adversarial Inference for Text-to-Image Synthesis

Thomas Fevens, Mohammad Havaei, Lisa Di-Jorio, 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

Partitioning a Polygon into Two Mirror Congruent Pieces

Günter Rote, Thomas Fevens, John Iacono, 2008, CCCG.

Web–Based Framework For Breast Cancer Classification

Thomas Fevens, Adam Krzyzak, Lukasz Jelen, 2014, J. Artif. Intell. Soft Comput. Res..

Comparison using the statistical test method ( sorted by score from high to low ) WEB – BASED FRAMEWORK FOR BREAST CANCER CLASSIFICATION

A. Krzyżak, T. Fevens, Łukasz Jeleń, 2015 .

Nuclei Segmentation in Histopathological Images Using Two-Stage Learning

Thomas Fevens, Qicheng Lao, Qingbo Kang, 2019, MICCAI.

Semi-automatic computer aided lesion detection in dental X-rays using variational level set

Adam Krzyzak, Song Li, Chao Jin, 2007, Pattern Recognit..

GLCM AND GLRLM BASED TEXTURE FEATURES FOR COMPUTER-AIDED BREAST CANCER DIAGNOSIS

Adam Krzyżak, Andrzej Obuchowicz, Thomas Fevens, 2012 .

Computer-Aided Breast Cancer Diagnosis Based on the Analysis of Cytological Images of Fine Needle Biopsies

Roman Monczak, Adam Krzyzak, Thomas Fevens, 2013, IEEE Transactions on Medical Imaging.

Absorbing Boundary Conditions for the Schrödinger Equation

Hong Jiang, Thomas Fevens, T. Fevens, 1999, SIAM J. Sci. Comput..

ABSORBING BOUNDARY CONDITIONS FOR THE SCHR ¨ ODINGER EQUATION

Thomas Fevens, Hong Jiang, T. Fevens, 1999 .

Cytological malignancy grading systems for fine needle aspiration biopsies of breast cancer

Adam Krzyzak, Thomas Fevens, Lukasz Jelen, 2017, 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Boosting Segmentation Performance across Datasets using Histogram Specification with Application to Pelvic Bone Segmentation

Prabhakara Subramanya Jois, Aniketh Manjunath, Thomas Fevens, 2021, 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Motion learning-based framework for unarticulated shape animation

Chao Jin, Shuo Li, Sudhir P. Mudur, 2007, The Visual Computer.

On the Effectiveness of Generative Adversarial Network on Anomaly Detection pdf

Thomas Fevens, Laya Rafiee Sevyeri, T. Fevens, 2021, ArXiv.

Deep Neural Networks for Breast Cancer Diagnosis: Fine Needle Biopsy Scenario

Bartosz Miselis, Thomas Fevens, Adam Krzyżak, 2019, Advances in Intelligent Systems and Computing.

Counting of RBCs and WBCs in noisy normal blood smear microscopic images

Adam Krzyzak, Thomas Fevens, Mehdi Habibzadeh, 2011, Medical Imaging.

APPLICATION OF PATTERN RECOGNITION TECHNIQUES FOR THE ANALYSIS OF THIN BLOOD SMEAR IMAGES

Adam Krzyżak, Thomas Fevens, Mehdi Habibzadeh, 2011 .

Fast and Robust Clinical Triple-Region Image Segmentation Using One Level Set Function

Adam Krzyzak, Song Li, Chao Jin, 2006, MICCAI.

Toward Automatic Computer Aided Dental X-ray Analysis Using Level Set Method

Thomas Fevens, Adam Krzyżak, Song Li, 2005, MICCAI.

Algorithms for Computing Geometric Measures of Melodic Similarity

Godfried T. Toussaint, Tomomi Matsui, Stefan Langerman, 2006, Computer Music Journal.

Computing a Geometric Measure of the Similarity Between two Melodies

Tomomi Matsui, Stefan Langerman, David Rappaport, 2003 .

Inference and Design in Kuba and Zillij Art with Shape Grammars

Thomas Fevens, Dania El-Khechen, Ramgopal Rajagopalan, 2006 .

FoCL: Feature-Oriented Continual Learning for Generative Models pdf

Thomas Fevens, Mohammad Havaei, Francis Dutil, 2020, Pattern Recognit..

Computer aided root lesion detection using level set and complex wavelets

Adam Krzyzak, Song Li, Chao Jin, 2007, SPIE Medical Imaging.

Automatic clinical image segmentation using pathological modeling, PCA and SVM

A. Krzyżak, T. Fevens, S. Li, 2006, Eng. Appl. Artif. Intell..

An automatic variational level set segmentation framework for computer aided dental X-rays analysis in clinical environments

Adam Krzyzak, Song Li, Shuo Li, 2006, Comput. Medical Imaging Graph..

Automatic Clinical Image Segmentation Using Pathological Modelling, PCA and SVM

Adam Krzyzak, Song Li, Shuo Li, 2005, MLDM.

Image Segmentation Adapted for Clinical Settings by Combining Pattern Classification and Level Sets

Adam Krzyzak, Shuo Li, Thomas Fevens, 2004, MICCAI.

A SVM-based framework for autonomous volumetric medical image segmentation using hierarchical and coupled level sets

Adam Krzyzak, Shuo Li, Thomas Fevens, 2004, CARS.

Robust nuclei segmentation in cyto-histopathological images using statistical level set approach with topology preserving constraint

Tien D. Bui, Thomas Fevens, T. D. Bui, 2017, Medical Imaging.

Local Algorithms for Dominating and Connected Dominating Sets of Unit Disk Graphs with Location Aware Nodes

Jorge Urrutia, Jurek Czyzowicz, Jaroslav Opatrny, 2008, LATIN.

Environment Lighting for Point Sampled Geometry

Feng Liu, Sudhir P. Mudur, Sushil Bhakar, 2006, International Conference on Computer Graphics, Imaging and Visualisation (CGIV'06).

Source-free Domain Adaptation Requires Penalized Diversity

Laya Rafiee Sevyeri, S. Kahou, T. Fevens, 2023, ArXiv.

' s personal copy Power-aware semi-beaconless 3 D georouting algorithms using adjustable transmission ranges for wireless ad hoc and sensor networks

T. Fevens, I. Stojmenovic, J. Opatrny, 2009 .

Survival backup strategy for controller placement problem in Software Defined Networking

T. Fevens, Y. Khamayseh, Abdunasser Alowa, 2021, Comput. Commun..

High delivery rate position-based routing algorithms for 3D ad hoc networks

Jaroslav Opatrny, Alaa Eddien Abdallah, Thomas Fevens, 2008, Comput. Commun..

To Veer or Not to Veer: Learning from Experts How to Stay Within the Crosswalk

Jeremy R. Cooperstock, Thomas Fevens, Roger Girgis, 2017, 2017 IEEE International Conference on Computer Vision Workshops (ICCVW).

AD-CGAN: Contrastive Generative Adversarial Network for Anomaly Detection

Laya Rafiee Sevyeri, T. Fevens, 2022, ICIAP.

Comparative study of shape, intensity and texture features and support vector machine for white blood cell classification

Adam Krzyżak, Thomas Fevens, Mehdi Habibzadeh, 2013 .

Influence of feature set reduction on breast cancer malignancy classification of fine needle aspiration biopsies

Adam Krzyzak, Thomas Fevens, Michal Jelen, 2016, Comput. Biol. Medicine.

Towards Minimum Inter-Controller Delay Time in Software Defined Networking

Thomas Fevens, Abdunasser Alowa, T. Fevens, 2020, FNC/MobiSPC.

The Concordia NLG Surface Realizer at SRST 2019

Thomas Fevens, Farhood Farahnak, Leila Kosseim, 2019, EMNLP.

Hybrid Position-Based Routing Algorithms for 3D Mobile Ad Hoc Networks

Song Liu, Alaa Eddien Abdallah, Thomas Fevens, 2008, 2008 The 4th International Conference on Mobile Ad-hoc and Sensor Networks.

Oversampling Methods for Classification of Imbalanced Breast Cancer Malignancy Data

Adam Krzyzak, Bartosz Krawczyk, Thomas Fevens, 2012, ICCVG.

Influence of nuclei segmentation on breast cancer malignancy classification

Adam Krzyzak, Thomas Fevens, Lukasz Jelen, 2009, Medical Imaging.

Classification of Breast Cancer Malignancy Using Cytological Images of Fine Needle Aspiration Biopsies

Adam Krzyzak, Thomas Fevens, Lukasz Jelen, 2008, Int. J. Appl. Math. Comput. Sci..

Leveraging Disease Progression Learning for Medical Image Recognition

Thomas Fevens, Qicheng Lao, T. Fevens, 2018, 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Unsupervised Anomaly Detection with a GAN Augmented Autoencoder

Thomas Fevens, Laya Rafiee, T. Fevens, 2020, ICANN.

Simple Polygons with an Innnite Sequence of Deeations

Michael A. Soss, T. Fevens, Pat Morin, 2001 .

Minimum convex partition of a constrained point set

Henk Meijer, David Rappaport, Thomas Fevens, 2001, Discret. Appl. Math..