Automatic design of pulse coupled neurons for image segmentation
暂无分享,去创建一个
Roland Olsson | Thomas Lindblad | Henrik Berg | José Chilo | Roland Olsson | T. Lindblad | Henrik Berg | J. Chilo | R. Olsson
[1] Paul Wintz,et al. Digital image processing (2nd ed.) , 1987 .
[2] Daniel P. Huttenlocher,et al. Efficient Graph-Based Image Segmentation , 2004, International Journal of Computer Vision.
[3] Daniel Matolin,et al. Cellular pulse-coupled neural network with adaptive weights for image segmentation and its VLSI implementation , 2004, IS&T/SPIE Electronic Imaging.
[4] Heggere S. Ranganath,et al. Perfect image segmentation using pulse coupled neural networks , 1999, IEEE Trans. Neural Networks.
[5] Hans-Paul Schwefel,et al. Evolution and optimum seeking , 1995, Sixth-generation computer technology series.
[6] Heggere S. Ranganath,et al. A neural network for image understanding , 1997 .
[7] Bart Selman,et al. Local search strategies for satisfiability testing , 1993, Cliques, Coloring, and Satisfiability.
[8] Juha A. Karvonen,et al. Baltic Sea ice SAR segmentation and classification using modified pulse-coupled neural networks , 2004, IEEE Transactions on Geoscience and Remote Sensing.
[9] Anthony Skjellum,et al. A High-Performance, Portable Implementation of the MPI Message Passing Interface Standard , 1996, Parallel Comput..
[10] Jason M. Kinser,et al. Image object signatures from centripetal autowaves , 2000, Pattern Recognit. Lett..
[11] Erkki Oja,et al. Principal components, minor components, and linear neural networks , 1992, Neural Networks.
[12] David R. Harris. Staff and Students of the Institute in 1997-1998 , 1997 .
[13] Xuelong Li,et al. Supervised Tensor Learning , 2005, ICDM.
[14] Alan F. Murray,et al. IEEE International Conference on Neural Networks , 1997 .
[15] Hans-Paul Schwefel,et al. Evolution and Optimum Seeking: The Sixth Generation , 1993 .
[16] Karina Waldemark,et al. Patterns from the sky: Satellite image analysis using pulse coupled neural networks for pre-processing, segmentation and edge detection , 2000, Pattern Recognit. Lett..
[17] K. Holsinger. The neutral theory of molecular evolution , 2004 .
[18] Jason M. Kinser,et al. Image Processing using Pulse-Coupled Neural Networks , 1998, Perspectives in Neural Computing.
[19] Bir Bhanu,et al. Adaptive image segmentation using a genetic algorithm , 1989, IEEE Transactions on Systems, Man, and Cybernetics.
[20] Mubarak Shah,et al. Motion layer extraction in the presence of occlusion using graph cuts , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[21] Simon Haykin,et al. Neural Networks: A Comprehensive Foundation , 1998 .
[22] Teuvo Kohonen,et al. Self-Organizing Maps , 2010 .
[23] Rafael C. González,et al. Local Determination of a Moving Contrast Edge , 1985, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[24] Bir Bhanu,et al. Adaptive integrated image segmentation and object recognition , 2000, IEEE Trans. Syst. Man Cybern. Part C.
[25] Hugo Guterman,et al. An adaptive neuro-fuzzy system for automatic image segmentation and edge detection , 2002, IEEE Trans. Fuzzy Syst..
[26] David Jones. High performance , 1989, Nature.
[27] Roland Olsson,et al. Inductive Functional Programming Using Incremental Program Transformation , 1995, Artif. Intell..
[28] Janet Wiles,et al. A comparison of neutral landscapes - NK, NKp and NKq , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).
[29] Reinhard Eckhorn,et al. Feature Linking via Synchronization among Distributed Assemblies: Simulations of Results from Cat Visual Cortex , 1990, Neural Computation.
[30] Jitendra Malik,et al. Normalized cuts and image segmentation , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[31] John L. Johnson,et al. PCNN models and applications , 1999, IEEE Trans. Neural Networks.
[32] Heggere S. Ranganath,et al. Object detection using pulse coupled neural networks , 1999, IEEE Trans. Neural Networks.
[33] Martin A. Riedmiller,et al. A direct adaptive method for faster backpropagation learning: the RPROP algorithm , 1993, IEEE International Conference on Neural Networks.