CHAPTER 1 INTRODUCTION
1.1. Market Definition
1.2. Executive Summary
1.3. The Scope of the Study
CHAPTER 2 RESEARCH METHODOLOGY
2.1. Secondary Research
2.2. Primary Research
2.3. Analytic Tools and Model
2.4. Economic Indicator
2.4.1. Base Year, Base Currency, Forecasting Period
2.5. Expert Validation
2.6. Study Timeline
CHAPTER 3 MARKET ANALYSIS
3.1. Industry Value Chain Analysis
3.2. Porter's Five Force Analysis
3.2.1. Bargaining Power of Buyers
3.2.2. Bargaining Power of Suppliers
3.2.3. Threats of Substitutes
3.2.4. Threats of New Entrants
3.2.5. Degree of Competition
3.3. PESTLE Analysis
3.3.1. Political
3.3.2. Economical
3.3.3. Social
3.3.4. Technological
3.3.5. Legal
3.3.6. Environmental
3.4. SWOT Analysis
3.4.1. Strengths
3.4.2. Weakness
3.4.3. Opportunities
3.4.4. Threats
3.5. Y-O-Y Analysis
CHAPTER 4 MARKET DYNAMICS
4.1. Market Drivers
4.1.1. Increasing the availability of spatial data and analytical tools
4.1.2. Growing demand for predicting the solution
4.1.3. Image optimization is a major application focus for the neural network
4.2. Market Restraints & Challenges
4.2.1. Complexity in training multilayer neural networks
4.2.2. Lack of expertise and other operational challenges
4.2.3. Slow digitisation rate across emerging economies
4.3. Market Opportunities
4.3.1. Growing innovation across end-user verticals
4.3.2. Growing use of DNN in IoT
CHAPTER 5 GLOBAL NEURAL NETWORK SOFTWARE MARKET – BY COMPONENT
5.1. Neural Network Software
5.2. Services
5.3. Platform & Other Enabling Services
CHAPTER 6 GLOBAL NEURAL NETWORK SOFTWARE MARKET – BY TYPE
6.1. Data Mining & Archiving
6.2. Analytical Software
6.3. Optimization Software
6.4. Genetic Algorithm
6.5. Simulated Annealing
6.6. Visualization Software
CHAPTER 7 GLOBAL NEURAL NETWORK SOFTWARE MARKET – BY APPLICATION
7.1. Fraud Detection
7.2. Machine Diagnostics
7.3. Portfolio Management
7.4. Financial Forecasting
7.5. Process Modelling
7.6. Others
CHAPTER 8 GLOBAL NEURAL NETWORK SOFTWARE MARKET – BY END USER
8.1. Government Institutes
8.2. Defence Agencies
8.3. BFSI
8.4. Healthcare
8.5. Retail
8.6. Media
8.7. Logistics
8.8. Others
CHAPTER 9 GLOBAL NEURAL NETWORK SOFTWARE MARKET - BY GEOGRAPHY
9.1. Introduction
9.2. North America
9.2.1. U.S.
9.2.2. Canada
9.2.3. Mexico
9.2.4. Costa Rica
9.3. South America
9.3.1. Brazil
9.3.2. Argentina
9.3.3. Chile
9.3.4. Columbia
9.3.5. Others
9.4. Europe
9.4.1. U.K.
9.4.2. Germany
9.4.3. France
9.4.4. Italy
9.4.5. Spain
9.4.6. Russia
9.4.7. Netherlands
9.4.8. Switzerland
9.4.9. Poland
9.4.10. Others
9.5. Asia-Pacific
9.5.1. China
9.5.2. Japan
9.5.3. India
9.5.4. South Korea
9.5.5. Australia & New Zealand
9.5.6. Malaysia
9.5.7. Singapore
9.5.8. Others
9.6. Middle East & Africa
9.6.1. UAE
9.6.2. Saudi Arabia
9.6.3. Iran
9.6.4. Iraq
9.6.5. Qatar
9.6.6. South Africa
9.6.7. Algeria
9.6.8. Morocco
9.6.9. Nigeria
9.6.10. Egypt
9.6.11. Others
CHAPTER 10 GLOBAL NEURAL NETWORK SOFTWARE MARKET - COMPANY PROFILES
10.1. NVIDIA Corporation
10.2. HP Development Company, L.P.
10.3. Google Inc.
10.4. International Business Machines Corporation
10.5. SAP SE
10.6. Intel Corporation
10.7. Microsoft Corporation
10.8. DeepMind Technologies Limited
10.9. Qualcomm Technologies Inc.
10.10. Neural Technologies Ltd.
10.11. Ward Systems Inc.
10.12. Afiniti Inc.
10.13. Alyuda Research, LLC.
10.14. Ward Systems Group, Inc.
10.15. Slagkryssaren AB
CHAPTER 11 GLOBAL NEURAL NETWORK SOFTWARE MARKET - COMPETITIVE LANDSCAPE
11.1. Market Share Analysis
11.2. Strategies adopted by top companies
11.3. Mergers, Acquisitions, Collaborations & Agreements
CHAPTER 12 MARKET INSIGHTS
12.1. Industry Experts Insights
12.2. Analysts Opinions
12.3. Investment Opportunities
CHAPTER 13 APPENDIX
13.1. List of Tables
13.2. List of Figures
