Deep Learning Algorithms

Erscheinungsjahr 2022
ISBN: 978-1-77469-362-9
Verlag: Arcler Press
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 408 Seiten, Electronic book text, Format (B × H): 152 mm x 229 mm

This book covers different topics from deep learning algorithms, including: methods and approaches for deep learning, deep learning applications in biology, deep learning applications in medicine, and deep learning applications in pattern recognition systems.Section 1 focuses on methods and approaches for deep learning, describing advancements in deep learning theory and applications - perspective in 2020 and beyond; deep ensemble reinforcement learning with multiple deep deterministic policy gradient algorithm; dynamic decision-making for stabilized deep learning software platforms; deep learning for hyperspectral data classification through exponential momentum deep convolution neural networks; and ensemble network architecture for deep reinforcement learning.Section 2 focuses on deep learning applications in biology, describing fish detection using deep learning; deep learning identification of tomato leaf disease; deep learning for plant identification in natural environment; and applying deep learning models to mouse behavior recognition.Section 3 focuses on deep learning applications in medicine, describing application of deep learning in neuroradiology: brain hemorrhage classification using transfer learning; a review of the application of deep learning in brachytherapy; exploring deep learning and transfer learning for colonic polyp classification; and deep learning algorithm for brain-computer interface.Section 4 focuses on deep learning applications in pattern recognition systems, describing application of deep learning in airport visibility forecast; hierarchical representations feature deep learning for face recognition; review of research on text sentiment analysis based on deep learning; classifying hand written digits with deep learning; and bitcoin price prediction based on deep learning methods.

Fachgebiete

• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Software Engineering
• Mathematik | Informatik EDV | Informatik EDV & Informatik Allgemein

Inhaltsverzeichnis

- Section 1: Methods and Approaches for Deep Learning
- Chapter 1 Advancements in Deep Learning Theory and Applications: Perspective in 2020 and Beyond
- Chapter 2 Deep Ensemble Reinforcement Learning With Multiple Deep Deterministic Policy Gradient Algorithm
- Chapter 3 Dynamic Decision-Making For Stabilized Deep Learning Software Platforms
- Chapter 4 Deep Learning For Hyperspectral Data Classification Through Exponential Momentum Deep Convolution Neural Networks
- Chapter 5 Ensemble Network Architecture for Deep Reinforcement LearningSection 2: Deep Learning Techniques Applied in Biology
- Chapter 6 Fish Detection Using Deep Learning
- Chapter 7 Can Deep Learning Identify Tomato Leaf Disease?
- Chapter 8 Deep Learning For Plant Identification In Natural Environment
- Chapter 9 Applying Deep Learning Models to Mouse Behavior RecognitionSection 3: Deep learning Applications in Medicine
- Chapter 10 Application of Deep Learning in Neuroradiology: Brain Hemorrhage Classification Using Transfer Learning
- Chapter 11 A Review of the Application of Deep Learning in Brachytherapy
- Chapter 12 Exploring Deep Learning and Transfer Learning for Colonic Polyp Classification
- Chapter 13 Deep Learning Algorithm For Brain-Computer InterfaceSection 4: Deep Learning in Pattern Recognition Tasks
- Chapter 14 The Application of Deep Learning In Airport Visibility Forecast
- Chapter 15 Hierarchical Representations Feature Deep Learning For Face Recognition
- Chapter 16 Review of Research on Text Sentiment Analysis Based on Deep Learning
- Chapter 17 Classifying Hand Written Digits With Deep Learning
- Chapter 18 Bitcoin Price Prediction Based on Deep Learning Methods

Über Autor(innen)

Dr. Zoran Gacovski has earned his PhD degree at Faculty of Electrical engineering, Skopje. His research interests include Intelligent systems and Software engineering, fuzzy systems, graphical models (Petri, Neural and Bayesian networks), and IT security. He has published over 50 journal and conference papers, and he has been reviewer of renowned Journals. Currently, he is a professor in Computer Engineering at European University, Skopje, Macedonia.