top

  Info

  • Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.

  Info

  • Utilizzare questo link per rimuovere la selezione effettuata.
Intelligent Computing in Carcinogenic Disease Detection
Intelligent Computing in Carcinogenic Disease Detection
Autore Das Sharma Kaushik
Edizione [1st ed.]
Pubbl/distr/stampa Singapore : , : Springer, , 2024
Descrizione fisica 1 online resource (189 pages)
Altri autori (Persone) KarSubhajit
MaitraMadhubanti
Collana Computational Intelligence Methods and Applications Series
ISBN 981-9724-24-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Contents -- List of Abbreviations -- 1 Introduction -- 1.1 Introduction -- 1.2 Historical Background of Carcinogenic Disease Detection -- 1.3 Intelligent Computing Tools in Carcinogenic Disease Detection and Classification -- 1.3.1 Image Processing Tools -- 1.3.2 Machine Learning Tools -- 1.3.2.1 Supervised Learning and Unsupervised Learning -- 1.3.2.2 Cross-Validation and Blind Test -- 1.3.2.3 Filter and Wrapper Methods -- 1.3.3 Modern Optimization Tools -- 1.4 Organization of the Book -- 1.5 Summary -- References -- 2 Biological Background of Benchmark Carcinogenic Data Sets -- 2.1 Introduction -- 2.2 Benchmark Carcinogenic Data Set I -- 2.2.1 Mathematical Representation of Microarray Gene Expression Data -- 2.2.2 Benchmark Microarray Gene Expression Data Sets -- 2.3 Benchmark Carcinogenic Data Set II -- 2.3.1 Microscopic Blood Smear Images -- 2.4 Benchmark Carcinogenic Data Set III -- 2.4.1 CT Images -- 2.5 Summary -- References -- 3 Intelligent Computing Approaches for Carcinogenic Disease Detection: A Review -- 3.1 Introduction -- 3.2 Intelligent Computing Approaches for Benchmark Carcinogenic Data Set I -- 3.3 Intelligent Computing Approaches for Benchmark Carcinogenic Data Set II -- 3.4 Intelligent Computing Approaches for Benchmark Carcinogenic Data Set III -- 3.5 Summary -- References -- 4 Classical Approaches in Gene Evaluation for Carcinogenic Disease Detection -- 4.1 Introduction -- 4.2 Filter Approaches in Gene Evaluation -- 4.2.1 T-Test Technique -- 4.2.2 Chi-Square Technique -- 4.2.3 Signal-to-Noise Ratio Technique -- 4.3 Wrapper Approaches in Gene Evaluation -- 4.3.1 Particle Swarm Optimization (PSO) -- 4.3.2 PSO-Based Wrapper Method for Gene Selection -- 4.4 Classifiers -- 4.4.1 Support Vector Machine (SVM) Classifier -- 4.4.2 k-Nearest Neighbor Classifier -- 4.5 Experimental Study.
4.5.1 Experimental Study on Filter Approaches -- 4.5.2 Experimental Study on Wrapper Approaches -- 4.6 Summary -- References -- 5 Intelligent Computing Approach in Gene Evaluation for Carcinogenic Disease Detection -- 5.1 Introduction -- 5.2 Adaptive k-Nearest Neighborhood Technique -- 5.2.1 PSO-Based Adaptive k-Nearest Neighborhood Technique for Gene Evaluation -- 5.2.2 Fitness Function -- 5.3 Experimental Study -- 5.4 Analysis of Experimental Results -- 5.4.1 Analysis of SRBCT Data Set -- 5.4.2 Analysis of ALL_AML Data Set -- 5.4.3 Analysis of MLL Data Set -- 5.5 Summary -- References -- 6 Intelligent Computing Approach for Leukocyte Identification -- 6.1 Introduction -- 6.2 Preprocessing -- 6.2.1 Identification of Leukocytes -- 6.2.2 Separation of Grouped Leukocytes -- 6.2.3 Image Cleaning -- 6.2.4 Separation of Whole Leukocyte, Nucleus, and Cytoplasm -- 6.3 Feature Extraction -- 6.4 Weighted Aggregation-Based Transposition PSO for Feature Evaluation -- 6.4.1 WATPSO-Based Feature Selection Technique -- 6.5 Experimental Study -- 6.5.1 Database -- 6.5.2 Performance Measure -- 6.5.3 Performance Evaluation -- 6.5.4 Comparative Study with Other Related Works Utilizing ALL Image Data -- 6.6 Summary -- References -- 7 Intelligent Computing Approach for Lung Nodule Detection -- 7.1 Introduction -- 7.2 Preprocessing -- 7.2.1 Lung Segmentation -- 7.2.2 Volumetric Shape Index -- 7.2.3 Multi-scale Dot Enhancement Filter -- 7.3 Lung Nodule Detection and Classification Methodology -- 7.3.1 Harmony Search Algorithm -- 7.3.2 Fitness Function -- 7.3.3 Adaptive Weight Selection Strategy -- 7.3.4 GrIHS-Based Feature Selection Strategy -- 7.4 Experimental Study -- 7.4.1 Result Analysis -- 7.5 Summary -- References -- 8 Conclusion -- 8.1 Future Research Directions -- Index.
Record Nr. UNINA-9910861098403321
Das Sharma Kaushik  
Singapore : , : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Intelligent Control : A Stochastic Optimization Based Adaptive Fuzzy Approach / / by Kaushik Das Sharma, Amitava Chatterjee, Anjan Rakshit
Intelligent Control : A Stochastic Optimization Based Adaptive Fuzzy Approach / / by Kaushik Das Sharma, Amitava Chatterjee, Anjan Rakshit
Autore Das Sharma Kaushik
Edizione [1st ed. 2018.]
Pubbl/distr/stampa Singapore : , : Springer Singapore : , : Imprint : Springer, , 2018
Descrizione fisica 1 online resource (XVI, 302 p. 159 illus., 146 illus. in color.)
Disciplina 006.3
Collana Cognitive Intelligence and Robotics
Soggetto topico Computational intelligence
Control engineering
Robotics
Mechatronics
Probabilities
Mathematical optimization
Optical data processing
Computational Intelligence
Control, Robotics, Mechatronics
Probability Theory and Stochastic Processes
Optimization
Image Processing and Computer Vision
ISBN 9789811312984
981-13-1298-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Part 1_ Prologue -- Chapter 1. Intelligent Adaptive Fuzzy Control -- Chapter 2. Some Contemporary Stochastic Algorithms: A Glimps -- Chpater 3. Fuzzy Controller Design-I: Stochastic Algorithm Based Approac -- Part II_Lyapunov Strategy Based Design Methodologie -- Chapter 4. Fuzzy Controller Design-II: Lyapunov Strategy Based Adaptive Approac -- Chapter 5. Fuzzy Controller Design-III: Hybrid Adaptive Approache -- Part III_H∞ Strategy Based Design Methodologies -- Chapter 6. Fuzzy Controller Design-IV: H∞ Strategy Based Robust Approac -- Chapter 7. Fuzzy Controller Design-V: Robust Hybrid Adaptive Approaches -- Part IV _Applications -- Chapter 8. Experimental Study-I: Temperature Control of an Air Heater System with Transportation Delay -- Chapter 9. Experimental Study-II: Vision Based Control of Robot Manipulators -- Chapter 10. Experimental Study-III: Vision Based Navigation of Mobile Robots -- Part V_Epilogue -- Chapter 11. Emerging Areas in Intelligent Fuzzy Control and Future Research Scopes.
Record Nr. UNINA-9910349473203321
Das Sharma Kaushik  
Singapore : , : Springer Singapore : , : Imprint : Springer, , 2018
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui