咨询与建议

限定检索结果

文献类型

  • 58 篇 会议
  • 13 篇 期刊文献

馆藏范围

  • 71 篇 电子文献
  • 0 种 纸本馆藏

日期分布

学科分类号

  • 24 篇 工学
    • 18 篇 计算机科学与技术...
    • 12 篇 软件工程
    • 5 篇 控制科学与工程
    • 3 篇 建筑学
    • 2 篇 电气工程
    • 2 篇 信息与通信工程
    • 1 篇 力学(可授工学、理...
    • 1 篇 动力工程及工程热...
    • 1 篇 土木工程
    • 1 篇 化学工程与技术
    • 1 篇 生物工程
    • 1 篇 安全科学与工程
  • 9 篇 理学
    • 7 篇 数学
    • 2 篇 系统科学
    • 1 篇 物理学
    • 1 篇 化学
    • 1 篇 生物学
  • 5 篇 管理学
    • 4 篇 图书情报与档案管...
    • 1 篇 管理科学与工程(可...
  • 1 篇 军事学

主题

  • 26 篇 pattern analysis
  • 23 篇 machine intellig...
  • 20 篇 system analysis ...
  • 19 篇 design engineeri...
  • 17 篇 neural networks
  • 12 篇 laboratories
  • 7 篇 systems engineer...
  • 7 篇 convergence
  • 6 篇 image segmentati...
  • 6 篇 voting
  • 5 篇 learning
  • 5 篇 pattern recognit...
  • 5 篇 genetic algorith...
  • 4 篇 neurons
  • 4 篇 computational in...
  • 4 篇 transfer functio...
  • 4 篇 mobile robots
  • 4 篇 humans
  • 4 篇 artificial neura...
  • 3 篇 multi-layer neur...

机构

  • 9 篇 pattern analysis...
  • 4 篇 pattern analysis...
  • 4 篇 pattern analysis...
  • 2 篇 pattern analysis...
  • 2 篇 pattern analysis...
  • 2 篇 electrical and c...
  • 2 篇 pattern analysis...
  • 2 篇 systems design e...
  • 2 篇 pattern analysis...
  • 2 篇 pattern analysis...
  • 2 篇 university of wa...
  • 2 篇 systems design e...
  • 2 篇 pattern analysis...
  • 2 篇 pattern analysis...
  • 2 篇 computer science...
  • 1 篇 electrical and c...
  • 1 篇 yonsei universit...
  • 1 篇 university of sc...
  • 1 篇 department of ma...
  • 1 篇 university of to...

作者

  • 13 篇 m. kamel
  • 11 篇 m.s. kamel
  • 7 篇 kamel mohamed
  • 5 篇 f. karray
  • 5 篇 hamid r. tizhoos...
  • 4 篇 mario ventresca
  • 4 篇 m.r. el-sakka
  • 4 篇 n.m. wanas
  • 3 篇 tizhoosh hamid r...
  • 3 篇 h.r. tizhoosh
  • 3 篇 m. ventresca
  • 3 篇 kamel mohamed s.
  • 3 篇 a.k.c. wong
  • 2 篇 kamel m
  • 2 篇 o. el badawy
  • 2 篇 bakus jan
  • 2 篇 hao li
  • 2 篇 abbas ahmadi
  • 2 篇 wanas nayer m.
  • 2 篇 farhang sahba

语言

  • 69 篇 英文
  • 2 篇 其他
检索条件"机构=Pattern Analysis And Machine Intelligence Laboratory Systems Design Eneering Department"
71 条 记 录,以下是1-10 订阅
排序:
Improving Generalization of Deep Neural Networks by Optimum Shifting
arXiv
收藏 引用
arXiv 2024年
作者: Zhou, Yuyan Li, Ye Feng, Lei Huang, Sheng-Jun MIIT Key Laboratory of Pattern Analysis and Machine Intelligence College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing211106 China Information Systems Technology and Design Pillar Singapore University of Technology and Design Singapore
Recent studies showed that the generalization of neural networks is correlated with the sharpness of the loss landscape, and flat minima suggests a better generalization ability than sharp minima. In this paper, we pr... 详细信息
来源: 评论
Distributed nonlinear model predictive control and metric learning for heterogeneous vehicle platooning with cut-in/cut-out maneuvers
arXiv
收藏 引用
arXiv 2020年
作者: Basiri, Mohammad Hossein Ghojogh, Benyamin Azad, Nasser L. Fischmeister, Sebastian Karray, Fakhri Crowley, Mark The Department of Systems Design Engineering University of Waterloo ON Canada The Department of Electrical and Computer Engineering University of Waterloo ON Canada The Smart Hybrid and Electric Vehicles Systems Lab The Real-Time Embedded Software Lab The Machine Learning Lab The Centre for Pattern Analysis and Machine Intelligence
Vehicle platooning has been shown to be quite fruitful in the transportation industry to enhance fuel economy, road throughput, and driving comfort. Model Predictive Control (MPC) is widely used in literature for plat... 详细信息
来源: 评论
Continual Learning in the Presence of Repetition
arXiv
收藏 引用
arXiv 2024年
作者: Hemati, Hamed Pellegrini, Lorenzo Duan, Xiaotian Zhao, Zixuan Xia, Fangfang Masana, Marc Tscheschner, Benedikt Veas, Eduardo Zheng, Yuxiang Zhao, Shiji Li, Shao-Yuan Huang, Sheng-Jun Lomonaco, Vincenzo van de Ven, Gido M. Institute for Computer Science University of St. Gallen Rosenbergstrasse 30 St. Gallen9000 Switzerland Department of Computer Science University of Bologna Via dell’Università 50 Cesena47521 Italy The University of Chicago 5801 S Ellis Ave Chicago60637 United States Argonne National Laboratory 9700 S Cass Ave Lemont60439 United States Graz University of Technology Rechbauerstraße 12 Graz8010 Austria TU Graz - SAL Dependable Embedded Systems Lab Silicon Austria Labs Graz8010 Austria Know-Center GmbH Sandgasse 36/4 Graz8010 Austria MIIT Key Laboratory of Pattern Analysis and Machine Intelligence Nanjing University of Aeronautics and Astronautics Nanjing211106 China Department of Computer Science University of Pisa Piano Secondo Largo Bruno Pontecorvo 3 Pisa56127 Italy Department of Electrical Engineering KU Leuven Kasteelpark Arenberg 10 Leuven3001 Belgium
Continual learning (CL) provides a framework for training models in ever-evolving environments. Although re-occurrence of previously seen objects or tasks is common in real-world problems, the concept of repetition in... 详细信息
来源: 评论
Why is the Winner the Best?
Why is the Winner the Best?
收藏 引用
Conference on Computer Vision and pattern Recognition (CVPR)
作者: M. Eisenmann A. Reinke V. Weru M. D. Tizabi F. Isensee T. J. Adler S. Ali V. Andrearczyk M. Aubreville U. Baid S. Bakas N. Balu S. Bano J. Bernal S. Bodenstedt A. Casella V. Cheplygina M. Daum M. De Bruijne A. Depeursinge R. Dorent J. Egger D. G. Ellis S. Engelhardt M. Ganz N. Ghatwary G. Girard P. Godau A. Gupta L. Hansen K. Harada M. Heinrich N. Heller A. Hering A. Huaulmé P. Jannin A. E. Kavur O. Kodym M. Kozubek J. Li H. Li J. Ma C. Martín-Isla B. Menze A. Noble V. Oreiller N. Padoy S. Pati K. Payette T. Rädsch J. Rafael-Patiño V. Singh Bawa S. Speidel C. H. Sudre K. Van Wijnen M. Wagner D. Wei A. Yamlahi M. H. Yap C. Yuan M. Zenk A. Zia D. Zimmerer D. Aydogan B. Bhattarai L. Bloch R. Brüngel J. Cho C. Choi Q. Dou I. Ezhov C. M. Friedrich C. Fuller R. R. Gaire A. Galdran Á. García Faura M. Grammatikopoulou S. Hong M. Jahanifar I. Jang A. Kadkhodamohammadi I. Kang F. Kofler S. Kondo H. Kuijf M. Li M. Luu T. Martinčič P. Morais M. A. Naser B. Oliveira D. Owen S. Pang J. Park S. Park S. Płotka E. Puybareau N. Rajpoot K. Ryu N. Saeed A. Shephard P. Shi D. Štepec R. Subedi G. Tochon H. R. Torres H. Urien J. L. Vilaça K. A. Wahid H. Wang J. Wang L. Wang X. Wang B. Wiestler M. Wodzinski F. Xia J. Xie Z. Xiong S. Yang Y. Yang Z. Zhao K. Maier-Hein P. F. Jäger A. Kopp-Schneider L. Maier-Hein Division of Intelligent Medical Systems German Cancer Research Center (DKFZ) Heidelberg Germany Helmholtz Imaging German Cancer Research Center (DKFZ) Heidelberg Germany Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany Division of Biostatistics German Cancer Research Center (DKFZ) Heidelberg Germany Division of Medical Image Computing German Cancer Research Center (DKFZ) Heidelberg Germany Faculty of Engineering and Physical Sciences School of Computing University of Leeds Leeds UK Institute of Informatics School of Management HES-SO Valais-Wallis University of Applied Sciences and Arts Western Switzerland Sierre Switzerland Department of Nuclear Medicine and Molecular Imaging Lausanne University Hospital Lausanne Switzerland Technische Hochschule Ingolstadt Ingolstadt Germany Center for Artificial Intelligence and Data Science for Integrated Diagnostics (AI2D) and Center for Biomedical Image Computing and Analytics (CBICA) University of Pennsylvania Philadelphia PA USA Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Department of Radiology Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Department of Radiology University of Washington Seattle WA USA Department of Computer Science Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS) University College London London UK Universitat Autònoma de Barcelona & Computer Vision Center Barcelona Spain Division of Translational Surgical Oncology National Center for Tumor Diseases (NCT/UCC) Dresden Dresden Germany Department of Advanced Robotics Istituto Italiano di Tecnologia Italy Department of Electronics Information and Bioengineering Politecnico di Milano Milan Italy IT University of Copenhagen Copenhagen Denmark Department of General Visceral and Transplantation Surgery Heidelberg University Hospital Heidelberg Germany Department of Radiology and Nuc
International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to investigating what can be learnt from t...
来源: 评论
Author Correction: Federated learning enables big data for rare cancer boundary detection
收藏 引用
Nature communications 2023年 第1期14卷 436页
作者: Sarthak Pati Ujjwal Baid Brandon Edwards Micah Sheller Shih-Han Wang G Anthony Reina Patrick Foley Alexey Gruzdev Deepthi Karkada Christos Davatzikos Chiharu Sako Satyam Ghodasara Michel Bilello Suyash Mohan Philipp Vollmuth Gianluca Brugnara Chandrakanth J Preetha Felix Sahm Klaus Maier-Hein Maximilian Zenk Martin Bendszus Wolfgang Wick Evan Calabrese Jeffrey Rudie Javier Villanueva-Meyer Soonmee Cha Madhura Ingalhalikar Manali Jadhav Umang Pandey Jitender Saini John Garrett Matthew Larson Robert Jeraj Stuart Currie Russell Frood Kavi Fatania Raymond Y Huang Ken Chang Carmen Balaña Jaume Capellades Josep Puig Johannes Trenkler Josef Pichler Georg Necker Andreas Haunschmidt Stephan Meckel Gaurav Shukla Spencer Liem Gregory S Alexander Joseph Lombardo Joshua D Palmer Adam E Flanders Adam P Dicker Haris I Sair Craig K Jones Archana Venkataraman Meirui Jiang Tiffany Y So Cheng Chen Pheng Ann Heng Qi Dou Michal Kozubek Filip Lux Jan Michálek Petr Matula Miloš Keřkovský Tereza Kopřivová Marek Dostál Václav Vybíhal Michael A Vogelbaum J Ross Mitchell Joaquim Farinhas Joseph A Maldjian Chandan Ganesh Bangalore Yogananda Marco C Pinho Divya Reddy James Holcomb Benjamin C Wagner Benjamin M Ellingson Timothy F Cloughesy Catalina Raymond Talia Oughourlian Akifumi Hagiwara Chencai Wang Minh-Son To Sargam Bhardwaj Chee Chong Marc Agzarian Alexandre Xavier Falcão Samuel B Martins Bernardo C A Teixeira Flávia Sprenger David Menotti Diego R Lucio Pamela LaMontagne Daniel Marcus Benedikt Wiestler Florian Kofler Ivan Ezhov Marie Metz Rajan Jain Matthew Lee Yvonne W Lui Richard McKinley Johannes Slotboom Piotr Radojewski Raphael Meier Roland Wiest Derrick Murcia Eric Fu Rourke Haas John Thompson David Ryan Ormond Chaitra Badve Andrew E Sloan Vachan Vadmal Kristin Waite Rivka R Colen Linmin Pei Murat Ak Ashok Srinivasan J Rajiv Bapuraj Arvind Rao Nicholas Wang Ota Yoshiaki Toshio Moritani Sevcan Turk Joonsang Lee Snehal Prabhudesai Fanny Morón Jacob Mandel Konstantinos Kamnitsas Ben Glocker Luke V M Dixon Matthew Williams Peter Zamp Center for Biomedical Image Computing and Analytics (CBICA) University of Pennsylvania Philadelphia PA USA. Department of Radiology Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Department of Informatics Technical University of Munich Munich Bavaria Germany. Intel Corporation Santa Clara CA USA. Department of Neuroradiology Heidelberg University Hospital Heidelberg Germany. Clinical Cooperation Unit Neuropathology German Cancer Consortium (DKTK) within the German Cancer Research Center (DKFZ) Heidelberg Germany. Department of Neuropathology Heidelberg University Hospital Heidelberg Germany. Division of Medical Image Computing German Cancer Research Center Heidelberg Germany. Pattern Analysis and Learning Group Department of Radiation Oncology Heidelberg University Hospital Heidelberg Germany. Neurology Clinic Heidelberg University Hospital Heidelberg Germany. Department of Radiology & Biomedical Imaging University of California San Francisco San Francisco CA USA. Symbiosis Center for Medical Image Analysis Symbiosis International University Pune Maharashtra India. Department of Neuroimaging and Interventional Radiology National Institute of Mental Health and Neurosciences Bangalore Karnataka India. Department of Radiology School of Medicine and Public Health University of Wisconsin Madison WI USA. Department of Medical Physics School of Medicine and Public Health University of Wisconsin Madison WI USA. Leeds Teaching Hospitals Trust Department of Radiology Leeds UK. Department of Radiology Brigham and Women's Hospital Harvard Medical School Boston MA USA. Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital Charlestown MA USA. Catalan Institute of Oncology Badalona Spain. Consorci MAR Parc de Salut de Barcelona Catalonia Spain. Department of Radiology (IDI
来源: 评论
Improving gradient-based learning algorithms for large scale feedforward networks
Improving gradient-based learning algorithms for large scale...
收藏 引用
International Joint Conference on Neural Networks (IJCNN)
作者: M. Ventresca H. R. Tizhoosh Faculty member of the Pattern Analysis and Machine Intelligence laboratory and Opposition-Based Learning Groups in the Systems Design Engineering Department University of Waterloo Waterloo ONT Canada
Large scale neural networks have many hundreds or thousands of parameters (weights and biases) to learn, and as a result tend to have very long training times. Small scale networks can be trained quickly by using seco... 详细信息
来源: 评论
Quasi-global oppositional fuzzy thresholding
Quasi-global oppositional fuzzy thresholding
收藏 引用
IEEE International Conference on Fuzzy systems (FUZZ-IEEE)
作者: Hamid R. Tizhoosh Farhang Sahba Pattern Analysis and Machine Intelligence Laboratory Systems Design Engineering University of Waterloo Waterloo ONT Canada University of Toronto Toronto ONT Canada
Opposition-based computing is the paradigm for incorporating entities along with their opposites within the search, optimization and learning mechanisms. In this work, we introduce the notion of "opposite fuzzy s... 详细信息
来源: 评论
Particle swarm clustering ensemble  08
Particle swarm clustering ensemble
收藏 引用
10th Annual Genetic and Evolutionary Computation Conference, GECCO 2008
作者: Ahmadi, Abbas Karray, Fakhri Kamel, Mohamed Pattern Analysis and Machine Intelligence Lab. Department of Systems Design Engineering University of Waterloo 200 University Avenue West Waterloo ON Canada
Extracting natural groups of the unlabeled data is known as clustering. To improve the stability and robustness of the clustering outputs, clustering ensembles have emerged recently. In this paper, an ensemble of part... 详细信息
来源: 评论
Numerical condition of feedforward networks with opposite transfer functions
Numerical condition of feedforward networks with opposite tr...
收藏 引用
International Joint Conference on Neural Networks (IJCNN)
作者: Mario Ventresca Hamid Reza Tizhoosh Pattern Analysis and Machine Intelligence (PAMI) laboratory in the Systems Design Engineering Department University of Waterloo Waterloo ONT Canada
Numerical condition affects the learning speed and accuracy of most artificial neural network learning algorithms. In this paper, we examine the influence of opposite transfer functions on the conditioning of feedforw... 详细信息
来源: 评论
Multiple Cooperating Swarms for Data Clustering
Multiple Cooperating Swarms for Data Clustering
收藏 引用
IEEE Swarm intelligence Symposium, SIS
作者: Abbas Ahmadi Fakhri Karray Mohamed Kamel Systems Design Engineering Department Pattern Analysis and Machine Intelligence Laboratory Waterloo ONT Canada Electrical and Computer Engineering Department Pattern Analysis and Machine Intelligence Laboratory Waterloo ONT Canada
A new clustering technique by the use of multiple swarms is proposed. The proposed technique mimics the behavior of biological swarms which explore food situated in several places. We model the clustering problem usin... 详细信息
来源: 评论