Deep Learning In Machine Vision Market Is Projected To Grow At A CAGR Of 55.60% Within The Forecast Period Of 2023-2030: Cognitive Market Research Themarketpublicist

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Deep Learning in Machine Vision Market Size, Share & Trends Analysis Report By Offering (Hardware, Software and Services), by Application (Inspection, Image Analysis, Anomaly Detection, Object Classification, Object Tracking, Counting, Bar Code Detection, Feature Detection, Location Detection, Optical Character Recognition, Face Recognition, Instance Segmentation, and Others), and by Object (Image and Video), And By Vertical (Electronics, Manufacturing, Automotive and Transportation, Food & Beverages, Aerospace, Healthcare, Building and Material, Power, and Others) By Region, And Segment Forecasts, 2023 – 2030

Market Overview

Deep learning in machine vision systems are those systems that can see and understand the world around them just like humans; those are the computers capable of understanding digital images and videos. Furthermore, the growth of deep learning in the machine vision market is increasing the adoption of AI, deep learning and technical advancements in hardware and software. The rising adoption of 3D inspection systems over conventional inspection systems is increasing, boosting the market's growth.

These developments empower businesses to offer better-tailored solutions and services, which, in turn, contribute to the growth of deep learning in the machine vision industry.

• For instance,Cadence Design Systems, Inc. has announced its widely acclaimed Tensilica Vision DSP product line by introducing two new DSP IP cores catering to embedded vision and AI. The leading-edge Cadence Tensilica Vision Q8 DSP boasts an impressive 3.8 tera operations per second (TOPS), delivering twice the performance and memory bandwidth of its predecessor, the Tensilica Vision Q7 DSP.

How COVID–19 Impacted the Deep Learning in Machine Vision Market?

The COVID-19 pandemic significantly impacted the Deep Learning in Machine Vision Market. While the market was experiencing steady growth before the pandemic, the global health crisis accelerated the adoption of machine vision systems powered by deep learning algorithms. The need for automation and contactless solutions in various industries, including healthcare, manufacturing, and retail, became more pronounced during the pandemic. Deep learning-based machine vision technologies enabled quality control, monitoring, and social distancing enforcement tasks. As a result, many businesses invested in these technologies to enhance operational efficiency and reduce human intervention, thereby driving the market's growth. The pandemic catalyzed the wider acceptance and implementation of deep learning in machine vision, setting the stage for continued expansion in the post-pandemic era.

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MARKET DYNAMICS: KEY DRIVERS

Advancements in Deep Learning Algorithms to Provide Viable Market Output

One of the primary drivers of Deep Learning in the Machine Vision Market is the continuous advancements in deep learning algorithms. Deep learning methods, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs), have demonstrated impressive abilities in detecting and identifying images and patterns. These algorithms are becoming increasingly sophisticated, enabling machines to accurately process and interpret visual data.

• Microsoft has recently unveiled the next stage of its extensive collaboration with OpenAL. This long-term partnership involves a substantial investment spanning multiple years and billions of dollars. The primary objective is to expedite advancements in Al technology, with the ultimate goal of making these benefits accessible on a global scale.

Large datasets that may be used to train deep neural networks have created new opportunities in a variety of fields, including autonomous cars, medical image analysis, and industrial quality control. Deep learning algorithms are improving the accuracy and speed of machine vision systems, which makes them more adaptable and appealing to a variety of sectors.

Growing Demand for Automation to Propel Market Growth

The growing demand for automation across industries. As businesses seek to improve operational efficiency, reduce production costs, and maintain consistent product quality, they turn to machine vision systems empowered by deep learning. These systems have the ability to carry out intricate functions, like identifying defects, recognizing objects, and analyzing gestures, at a speed and magnitude that exceeds what humans can achieve. Industries like automotive, electronics, and logistics are increasingly integrating deep learning-based machine vision solutions into their processes to ensure accuracy, minimize errors, and achieve higher productivity. The demand for automation, driven by factors like labor shortages, rising labor costs, and the need for 24/7 operations, is a significant growth driver in this market.

MARKET DYNAMICS: KEY RESTRAINTS

Data Privacy and Security Concerns to Hinder Market Growth

Data privacy and security issues significantly restrain the Deep Learning in Machine Vision Market. Deep learning algorithms rely heavily on vast datasets for training and continuous learning. However, collecting, storing, and utilizing sensitive visual data can raise concerns, especially in applications involving personal information, such as healthcare and surveillance. Ensuring compliance with data protection regulations, like HIPAA and GDPR, becomes a complex challenge for companies implementing machine vision systems. There is a growing need to balance leveraging machine vision for its advantages and safeguarding individuals' privacy rights. Addressing these concerns with robust data anonymization and encryption measures is vital to building trust and sustaining the market's growth. Additionally, the risk of data breaches and unauthorized access remains challenging, requiring continuous vigilance in an evolving threat landscape.

How are Segments Performing in the Global Deep Learning in Machine Vision Market?

Offering Segment Analysis

According to Cognitive Market Research, the software segment is both the dominant and fastest-growing. In order to build, train, and deploy neural networks for tasks like image recognition, object identification, and pattern analysis, deep learning significantly relies on sophisticated software. As the demand for machine vision solutions across industries like automotive, healthcare, manufacturing, and agriculture continues to surge, so does the need for powerful and versatile software tools. These software solutions include neural network frameworks, pre-trained models, and user-friendly development environments. They offer the flexibility to adapt to diverse use cases, making them a fundamental component of any machine vision system. Moreover, software providers continually update and enhance their offerings, staying at the forefront of technological advancements and keeping them at the market's helm.

The hardware segment has emerged as the fastest-growing segment hardware segment is the continuous technological advancements in machine vision hardware components. These hardware components include specialized GPUs (Graphics Processing Units), TPUs (Tensor Processing Units), and custom-designed AI accelerators. These advanced hardware components are purpose-built to handle the intensive computational requirements of deep learning algorithms, making them indispensable for high-performance machine vision applications. As deep learning models become more complex and sophisticated, businesses and organizations increasingly invest in powerful hardware to ensure faster processing speeds and improved accuracy.

Application Segment Analysis

The inspection application segment dominates in the Deep Learning in Machine Vision Market because of its wide-ranging applications across various industries. Inspection tasks involve examining products, components, and materials for defects, quality control, and adherence to specifications. Deep learning in machine vision has revolutionized inspection processes by enabling high-speed, accurate, and automated defect detection. Industries such as manufacturing, automotive, electronics, and pharmaceuticals heavily rely on machine vision inspection systems to ensure product quality, reduce production errors, and enhance efficiency.

According to Cognitive Market Research, THE object classification application segment is experiencing rapid growth primarily due to its relevance in various sectors, including e-commerce, autonomous vehicles, and robotics. Furthermore, object classification is vital for autonomous driving systems in the automotive industry. Vehicles equipped with deep learning-based vision can recognize and classify objects on the road, enhancing safety and navigation.

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Object Segment Analysis

According to Cognitive Market Research, the dominance of the image segment in the Deep Learning in Machine Vision Market can be attributed to its fundamental role in machine vision processes and its extensive range of applications across various industries. Image-based deep learning encompasses examining and understanding static images, making it a vital element for numerous applications. Furthermore, image-based machine vision is exceptionally adaptable and useful in diverse sectors such as manufacturing, healthcare, automotive, agriculture, etc. It is employed for quality control, defect detection, pattern recognition, and other purposes.

The video section is experiencing rapid growth in the deep learning in machine vision market. Video-based machine vision plays a crucial role in real-time surveillance and monitoring applications by enabling constant tracking of objects, individuals, or events in a dynamic setting. Additionally, autonomous vehicles and drones heavily depend on video-based machine vision for navigation, obstacle detection, and object recognition. With the increasing prominence of autonomous technologies, this sector is expected to experience substantial growth. Furthermore, video analytics in retail stores offer valuable insights into customer behavior, foot traffic, and store layout optimization, thereby contributing to the expansion of this segment.

Object Segment Analysis

According to Cognitive Market Research, the manufacturing sector is prominent in the Deep Learning in Machine Vision Market because it traditionally relies on automation and machine vision technologies. Industries such as electronics, automotive, and food and beverages greatly depend on deep learning in machine vision to ensure quality control and detect defects. These businesses may make sure that their goods fulfil high quality requirements by utilising automated inspection systems. Additionally, machine vision technology improves manufacturing efficiency and productivity by identifying bottlenecks, minimizing waste, and enhancing overall production processes.

The healthcare sector is experiencing rapid growth in deep learning in the machine vision market. This technology transforms medical imaging, enabling more accurate and efficient analysis of X-rays, MRIs, CT scans, and pathology slides. Advanced algorithms support radiologists and pathologists in diagnosing diseases with greater precision and speed. Additionally, machine vision is crucial in early disease detection, particularly in cancer screening. Identifying anomalies and potential health concerns in medical images facilitates timely interventions and enhances patient outcomes.

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Which Region Dominates the Market in 2023, and Which Region is Expanding at the Fastest CAGR?

According to Cognitive Market Research, North America, specifically the United States, has emerged as the dominant region in the Deep Learning in Machine Vision market due to a combination of key factors. The United States has a strong technological innovation and entrepreneurship ecosystem. Silicon Valley, in particular, is a global hub for cutting-edge research and development in artificial intelligence and deep learning, attracting top talent and substantial investment in machine vision technologies. This fosters a dynamic environment for innovation. The United States has a mature market for technology adoption. Industries such as healthcare, automotive, and manufacturing have eagerly embraced machine vision to enhance productivity and efficiency, driving significant growth in the sector. The United States benefits from a well-established network of leading universities, research institutions, and tech companies that actively collaborate on advancing deep learning techniques. This ensures a continuous flow of talent and breakthroughs.

The Asia-Pacific region's Deep Learning in Machine Vision market is experiencing rapid growth for various reasons. The region is home to some of the world's largest and fastest-growing economies, including China, India, and South Korea. These countries have been actively investing in technology infrastructure and manufacturing sectors, which has resulted in a higher demand for machine vision solutions. Industries such as electronics, automotive, and manufacturing increasingly rely on these solutions to improve automation, quality control, and operational efficiency. The Asia-Pacific region benefits from a large and highly skilled engineering and computer science workforce. This well-equipped workforce is actively contributing to developing and implementing deep learning in machine vision technologies.

COMPETITIVE LANDSCAPE: DEEP LEARNING IN THE MACHINE VISION MARKET

The machine vision market is characterized by fierce competition and diversity in deep learning. This sector encompasses many companies, varying from large multinational corporations to smaller niche businesses, all vying to provide innovative solutions, proficient translation and interpretation, and advanced deep learning technology. Globalization and advancements in technology drive such competition.

• January 2023: Visteon and Qualcomm Technologies, Inc. have unveiled their plans to enhance their technology partnership by creating a cutting-edge cockpit domain controller. This controller aims to empower automotive manufacturers worldwide to construct state-of-the-art cockpits for the future. By integrating Visteon's SmartCore software and Snapdragon Cockpit Platforms, automakers can swiftly implement advanced features and functionalities in their upcoming cockpits. These production programs are expected to be ready for launch by 2025.
• August 2023: IBM has partnered with the Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) to officially establish an Al Center of Excellence during the World Future Energy Summit of Abu Dhabi Sustainability Week . This collaboration seeks to enhance cooperation to enhance the utilization of Al technology and contribute to promoting sustainability.

Some Prominent Players in the Global Deep Learning in Machine Vision market include :

• Cognex Corporation
• Intel Corporation
• NATIONAL INSTRUMENTS CORP.
• SICK AG
• Datalogic S.p.A.
• STEMMER IMAGING AG
• Abto Software
• Adaptive Vision Sp. z o.o.
• Autonics Corporation
• Basler AG
• Cyth Systems, Inc.
• EURESYS S.A.
• IDS Imaging Development Systems GmbH
• Integro Technologies Corp.
• LeewayHertz
• Matrox Imaging
• MVTEC SOFTWARE GMBH
• Omron Microscan Systems, Inc.
• perClass BV
• Qualitas Technologies
• RSIP Vision
• USS Vision LLC
• Viska Automation Systems Ltd.
• T/A Viska Systems

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Market Summary :

• The global deep learning in machine vision market will expand at a significant rate of 55.60% CAGR between 2023 and 2030.
• The demand for deep learning in the machine vision market is rising due to theincreasing adoption of AI, deep learning and technical advancements in hardware and software.
• Demand for software remains higher in the deep learning in the machine vision market.
• The inspection category held the highest deep learning in machine vision market revenue share in 2023.
• North America will continue to lead, whereas the Asia Pacific deep learning in machine vision market will experience the strongest growth until 2030.

SEGMENTATION: Deep Learning in the Machine Vision Market

Offering Outlook :

• Hardware
• Software
• Services

Application Outlook :

• Inspection
• Image Analysis
• Anomaly Detection
• Object Classification
• Object Tracking
• Counting
• Bar Code Detection
• Feature Detection
• Location Detection
• Optical Character Recognition
• Face Recognition
• Instance Segmentation
• Others

Object Outlook :

• Image
• Video

Vertical Outlook :

• Electronics
• Manufacturing
• Automotive and Transportation
• Food & Beverages
• Aerospace
• Healthcare
• Building and Material
• Power
• Others

Regional Outlook :

• North America
  • The U.S.
  • Canada
  • Mexico
• Europe
  • Germany
  • France
  • UK
  • Italy
  • Spain
  • Rest of Europe
• Asia Pacific
  • China
  • Japan
  • India
  • South Korea
  • South East Asia
  • Rest of Asia Pacific
• Latin America
  • Brazil
  • Argentina
  • Rest of Latin America
• Middle East and Africa
  • GCC Countries
  • South Africa
  • Rest of MEA

Frequently asked questions about the global Deep Learning in Machine Vision market.

• What is the market size for the deep learning in machine vision market in 2023?

Answer- The global market size for the deep learning in machine vision market in 2023 was XX USD billion.

• What is the growth rate for deep learning in the machine vision market during the forecast period?

Answer- The global market is expected to grow with a CAGR of 55.60% during the forecast period.

• Which is the leading region of the market for deep learning in machine vision?

Answer- North America had the largest global deep learning in machine vision market revenue share in 2023.

• Which region is expected to witness the fastest growth in the coming years?

Answer- Asia Pacificwill witness the fastest growth in the global deep learning machine vision market over the coming years.

• Which is the leading country indeep learning in the machine vision market in 2023?

Answer- The United States had the largest global deep learning in machine vision market revenue share in 2023.

• What are the key drivers for the growth of deep learning in the machine vision market?

Answer- The main drivers of the growth of deep learning in the machine vision market are increasing adoption of AI, deep learning and technical advancements in hardware and software.

• Which is the major segment in the deep learning in the machine vision marketby Offering?

Answer- The software segment had the largest share in the global market by offering.

• Which is the major segment in the deep learning in the machine vision marketby object?

Answer- In 2023, the image segment had a major revenue share in the global market regarding objects.

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