000			05284nam a22004933u 4500
001			EBL1877028
006			m d
007			cr -n---------
008			170519s2015||||||| s|||||||||||eng|d
020			_a9781483297842 _c131.31 (NL),131.31 (UA),109.43 (3U),87.54 (1U)
035			_aEBL1877028
035			_a(OCoLC)651726536
040			_aAU-PeEL _beng _cAU-PeEL _dAU-PeEL
050		4	_aQ327 -- .P379 1994
082	0	0	_a006.4
090			_aQ327 -- .P379 1994
100	1		_aGelsema, E. S.
245	1	0	_aPattern Recognition in Practice IV : _bMultiple Paradigms, Comparative Studies and Hybrid Systems
260			_aAmsterdam : _bElsevier Science, _c2015.
300			_a1 online resource (593 p.)
490	0		_aeBooks on Demand
490	1		_aMachine Intelligence and Pattern Recognition ; _vv.Volume 16
505	0		_aFront Cover -- Pattem Recognition in Practice IV: Multiple Paradigms, Comparative Studies and Hybrid Systems -- Copyright Page -- Table of Contents -- PREFACE -- ACKNOWLEDGEMENTS -- PART I: PATTERN RECOGNITION -- Chapter 1. Patterns in the role of knowledge representation -- 1. INTRODUCEN -- 2. PATTERN REPRESENTATION -- 3. PATTERN RELATIONS -- 4. METMIC -- 5. HUMAN INTERACTION -- 6. PROJECTS -- 7. CONCLUSION -- APPENDIX -- REFERENCES -- Chapter 2. Application of evidence theory to k-NN pattern classification -- 1. D-S THEORY -- 2. THE METHOD -- 3. SIMULATION RESULTS -- 4. CONCLUSION
505	8		_aREFERENCES -- Chapter 3. Decision trees and domain knowledge in pattern recognition -- 1. INTRODUCTION -- 2. OVERVIEW OF DECISION TREE METHODOLOGIES -- 3. A FRAMEWORK FOR DECISION TREE CONSTRUCTION -- 4. EXPERIMENTAL EVALUATION -- 5. CONCLUSIONS -- REFERENCES -- Chapter 4. Object recognition using hidden Markov models -- 1. INTRODUCTION -- 2. STATISTICAL OBJECT RECOGNITION -- 3. HIDDEN MARKOV MODELS -- 4. OBJECT ORIENTED IMPLEMENTATION OF HMMS -- 5. AFFINE INVARIANT FEATURES -- 6. EXPERIMENTAL RESULTS -- 7. SUMMARY AND CONCLUSIONS -- ACKNOWLEDGEMENT -- REFERENCES
505	8		_aChapter 5. Inference of syntax for point sets -- 1. INTRODUCTION -- 2. CHUNKING -- 3. LOW ORDER MOMENT DESCRIPTORS -- 4. INFERENCE -- 5. GENERALISATION -- 6. INVARIANCE -- 7. NOISE -- 8. BINDING AND OCCLUSION -- 9. NEURAL MODELS -- 10. SUMMARY AND CONCLUSIONS -- REFERENCES -- Chapter 6. Recognising cubes in images -- 1. INTRODUCTION -- 2. FINDING LINE SEGMENTS -- 3. FINDING SQUARES -- 4. FINDING CUBES -- 5. NOISE -- 6. INVARIANCE AND MANIFOLDS -- 7. OCCLUSION -- 8. CONCLUSION -- REFERENCES -- Chapter 7. Syntactic pattern classification of moving objects in a domestic environment
505	8		_a1. INTRODUCTION -- 2. METHOD -- 3. RESULTS -- 4. ROBUSTNESS -- 5. CONCLUSION AND FURTHER WORK -- REFERENCES -- Chapter 8. Initializing the EM algorithm for use in Gaussian mixture modelling -- 1. INTRODUCTION -- 2. THE EM ALGORITHM -- 3. CONVERGENCE AND INITIAL CONDITIONS -- 4. CLUSTERING TECHNIQUES -- 5. THE DOG RABBIT STRATEGY -- 6. RESULTS -- 7. CONCLUSION AND SUMMARY -- REFERENCES -- Chapter 9. Predicting REM in sleep EEG using a structural approach -- 1. INTRODUCTION -- 2. MODELING FRAMEWORK -- 3. METHODOLOGY -- 4. EXAMPLE -- 5. CONCLUSIONS -- REFERENCES -- Discussions Part I: Paper Vamos
505	8		_aPART II: SIGNAL- AND IMAGE PROCESSING -- Chapter 10. On the problem of restoring original structure of signals (images) corrupted by noise -- 1. INTRODUCTION -- 2. PIECE-WISE-LINEAR REGRESSION -- 3. MODEL SELECTION PROBLEM -- 4. APPLICATION TO IMAGE ANALYSIS -- 5. ROBUST REGRESSION AND HOUGH TRANSFORM -- 6. SUMMARY -- REFERENCES -- Chapter 11. Reflectance ratios: An extension of Land's retinex theory -- 1. INTRODUCTION -- 2. REFLECTANCE RATIOS -- 3. RECOGNITION USING REFLECTANCE RATIOS -- 4. EXPERIMENTS -- 5. DISCUSSION -- REFERENCES -- Chapter 12. A segmentation algorithm based on AI techniques
505	8		_a1. INTRODUCTION
520			_aThe era of detailed comparisons of the merits of techniques of pattern recognition and artificial intelligence and of the integration of such techniques into flexible and powerful systems has begun. So confirm the editors of this fourth volume of Pattern Recognition in Practice, in their preface to the book. The 42 quality papers are sourced from a broad range of international specialists involved in developing pattern recognition methodologies and those using pattern recognition techniques in their professional work. The publication is divided into six sections: Pattern Recognition, Signal an
588			_aDescription based upon print version of record.
650		4	_aArtificial intelligence -- Congresses.
650		4	_aImage processing -- Congresses.
650		4	_aPattern perception -- Congresses.
650		4	_aSignal processing -- Congresses.
655		0	_aElectronic books.
700	1		_aKanal, L. N.
776	0	8	_iPrint version: _aGelsema, E. S. _tPattern Recognition in Practice IV: Multiple Paradigms, Comparative Studies and Hybrid Systems _dAmsterdam : Elsevier Science,c2015 _z9780444818928
830		0	_aMachine Intelligence and Pattern Recognition
856	4	0	_uhttp://uttyler.eblib.com/patron/FullRecord.aspx?p=1877028 _yClick here to view this ebook.
901			_aEBL
942			_cEBOOK _2lcc
999			_c874903 _d879328