Computer vision and image processing 4th International Conference, CVIP 2019, Jaipur, India, September 27-29, 2019, revised selected papers.: 4th International Conference, CVIP 2019, Jaipur, India, September 27-29, 2019, revised selected papers. Part II (©2020)

• Record Type: Book
• Further Information: Note: Neeta Nain, Santosh Kumar Vipparthi, Balasubramanian Raman (eds.).
• Other Names: Nain, Neeta; Vipparthi, Santosh Kumar; Raman, Balasubramanian; International Conference on Computer Vision and Image Processing, 4th
• Contents: Intro -- Preface -- Organization -- Contents -- Part II -- Contents -- Part I -- Neural Network -- Denoising Images with Varying Noises Using Autoencoders -- 1 Introduction -- 2 Background Work -- 3 Proposed Model -- 4 Experimental Setup and Results -- 5 Conclusion -- References -- Image Aesthetics Assessment Using Multi Channel Convolutional Neural Networks -- 1 Introduction -- 2 Deep Learning for IAA -- 2.1 CNN Architectures -- 2.2 Transfer Learning and Fine Tuning -- 3 Multi Channel CNN Based Image Aesthetic Assessment -- 3.1 Image Pre-processing and Feature Selection 3.2 Proposed Multi Channel CNN for IAA -- 4 Experiments -- 4.1 Comparison with Various Approaches -- 5 Conclusions -- References -- Profession Identification Using Handwritten Text Images -- 1 Introduction -- 2 Proposed Work -- 2.1 Acquisition of Dataset -- 2.2 Proposed Model -- 3 Experiments and Results -- 3.1 Training Phase -- 3.2 Testing Phase -- 3.3 Classification Report and Confusion Matrix -- 4 Conclusion -- References -- A Study on Deep Learning for Breast Cancer Detection in Histopathological Images -- Abstract -- 1 Introduction -- 1.1 Breast Cancer -- 2 Breast Histopatholgy 3 Deep Neural Network Architecture -- 4 Deep Learning for Breast Histopathology Analysis -- 4.1 Nuclei Analysis -- 4.2 Tubules Analysis -- 4.3 Epithelial and Stromal Region Analysis -- 4.4 Mitotic Activity Analysis -- 4.5 Other Tasks -- 5 Discussion, Conclusions and Future Works -- 5.1 Discussion -- 5.2 Conclusion -- 5.3 Future Works -- References -- Face Presentation Attack Detection Using Multi-classifier Fusion of Off-the-Shelf Deep Features -- 1 Introduction -- 2 Proposed Approach -- 3 Experiments and Results -- 4 Conclusion -- References Vision-Based Malware Detection and Classification Using Lightweight Deep Learning Paradigm -- Abstract -- 1 Introduction -- 1.1 Malware Analysis -- 1.2 Related Work -- 2 Proposed Methodology -- 2.1 Convolutional Neural Networks -- 3 Datasets -- 4 Experimental Results -- 5 Conclusion -- References -- A Deep Neural Network Classifier Based on Belief Theory -- 1 Introduction -- 1.1 Evidence Theory -- 1.2 Evidence Theoretic Classifier (ETC) -- 2 Belief Theory Based Hyper-Credal N.N. Classifier -- 2.1 The Framework of Basic Belief Assignment -- 2.2 Combining the Basic Belief Assignments 3 Belief Theory Based Hyper-Credal CNN Classifier -- 4 Results -- 5 Conclusion -- References -- Real-Time Driver Drowsiness Detection Using Deep Learning and Heterogeneous Computing on Embedded System -- 1 Introduction -- 2 The Prototype Network: DDDN -- 3 The Proposed Light-Weight DDDN -- 3.1 Deep Visualization and Pruning of DDDN-B4 -- 3.2 Rank Analysis Using VBMF -- 3.3 The Proposed Light DDDN Model (DDDN-L) -- 4 Experiment Discussions and Implementation Details -- 4.1 Dataset -- 4.2 CNN Training -- 4.3 Heterogeneous Computing Based Implementation -- 4.4 Results and Discussion -- 5 Conclusion
• Publisher Details: Singapore : Springer
• Publication Date: 2020
• Copyright Date: 2020
• Extent: 1 online resource (530 p.)
• Subjects: 006.3/7; Computer vision -- Congresses; Image processing -- Digital techniques -- Congresses; Computer vision; Image processing -- Digital techniques; Electronic books; Conference papers and proceedings
• Languages: English
• ISBNs: 9789811540189; 9811540187
• Notes: Note: Includes bibliographical references and index.
• 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.