The International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2019). ([2020])

• Record Type: Book
• Other Titles: AMLTA 2019
• Further Information: Note: Editors, Aboul Ella Hassanien, Ahmad Taher Azar, Tarek Gaber, Roheet Bhatnagar and Mohamed F. Tolba.
• Editors: Hassanien, Aboul Ella; Azar, Ahmad Taher; Gaber, Tarek, 1975-; Bhatnagar, Roheet; Tolba, Mohamed F
• Other Names: AMLTA (Conference)
• Contents: Intro; Preface; Organization; Honorary Chair; General Chair; International Advisory Board; Program Chairs; Publicity Chairs; Technical Program Committee; Local Arrangement Chairs; Keynote Speakers and Tutorial; Multi-modal and Uncertain Optimization with Differential Evolution -- Some Recent Approaches and Future Challenges; Modern Algorithms in Control and Design of Complex Systems; Hands-on to TensorFlow (Tutorial on); Contents; Deep Learning Applications; A Deep Learning Approach for Tongue Diagnosis; Abstract; 1 Introduction; 2 Tongue Image Syndrome Classification Model Based on CNN 2.1 Data Pre-processing Stage2.2 Deep Learning Stage; 3 Experiment; 3.1 Two-Class Experiment; 3.2 Three-Class Experiment; 4 Result; 5 Platform; 6 Discussion and Conclusion; Acknowledgements; References; Reduced 3-D Deep Learning Framework for Hyperspectral Image Classification; 1 Introduction; 2 Proposed Framework; 2.1 Hyperspectral Dimension Reduction; 2.2 3D Convolutional Neural Network; 3 Experimental Results; 3.1 Experimental Datasets; 3.2 Experimental Design; 3.3 Classification Results; 4 Conclusion; References An Efficient Deep Convolutional Neural Network for Visual Image Classification1 Introduction; 2 Related Work, Contribution, and Organization of this Paper; 3 The Proposed Deep Model (VICNet); 4 Experimental Evaluations; 4.1 ImageNet Dogs; 4.2 Features Classification; 4.3 Experimental Evaluation Metrics; 5 Results and Discussion; References; Deep Learning for Predictive Analytics in Healthcare; Abstract; 1 Introduction; 2 Deep Learning Predictive Analytics Survey in Health Care; 3 Deep Learning Framework for Healthcare Predictions; 3.1 Deep Learning Models 3.2 Framework of Deep Learning in Healthcare4 Deep Learning Tools; 5 Future Trends of Deep Learning in Healthcare Predictions; 6 Conclusion; References; Deep Layer CNN Architecture for Breast Cancer Histopathology Image Detection; Abstract; 1 Introduction; 2 The Proposed Deep Layer CNN Architecture for Breast Cancer Image Detection; 3 Performance Measure for Breast Cancer Image Detection; 4 Experimental Results; 5 Conclusion; Acknowledgement; References; Regression Task on Big Data with Convolutional Neural Network; 1 Introduction; 2 Methods and Data; 3 Experiments; 4 Result 5 Conclusion and Future WorkReferences; The Regression of MNIST Dataset Based on Convolutional Neural Network; 1 Introduction; 2 Method; 2.1 Established Relationship Between Regression and MNIST Dataset; 2.2 Description of the CNN in Deep Learning; 2.3 Predicting the Target of MNIST by the CNN; 3 Experiments and Results; 3.1 Establishing the Optimal Network Architecture; 3.2 Results of Regression with Labels of Different Standard Deviation; 4 Conclusion; References; Swarm Intelligence and Applications; Intelligent Hybrid Approach for Feature Selection; Abstract; 1 Introduction
• Publisher Details: Cham, Switzerland : Springer
• Publication Date: 2020
• Extent: 1 online resource, illustrations
• Subjects: 006.3/1; Machine learning -- Congresses; Artificial intelligence -- Congresses; COMPUTERS / General; Electronic books; Electronic books
• Languages: English
• ISBNs: 9783030141189; 3030141187
• Related ISBNs: 9783030141172
• Notes: Note: Includes bibliographical references and index.; Note: Online resource; title from PDF title page (EBSCO, viewed March 20, 2019).
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.