{"id":2155,"date":"2024-07-04T13:48:52","date_gmt":"2024-07-04T06:48:52","guid":{"rendered":"https:\/\/new-ocean.com.vn\/?post_type=article&p=2155"},"modified":"2024-07-04T16:48:58","modified_gmt":"2024-07-04T09:48:58","slug":"machine-learning-computer-vision","status":"publish","type":"article","link":"https:\/\/noas.new-ocean.com.vn\/en\/luu-tru\/article\/machine-learning-computer-vision","title":{"rendered":"Applications of AI: Computer Vision, Machine Learning, and Deep Learning"},"content":{"rendered":"

Tr\u00ed tu\u1ec7 Nh\u00e2n t\u1ea1o (AI) \u0111\u00e3 kh\u00f4ng c\u00f2n l\u00e0 m\u1ed9t kh\u00e1i ni\u1ec7m xa l\u1ea1 trong th\u1eddi k\u1ef3 C\u00f4ng ngh\u1ec7 4.0. Tr\u00ed tu\u1ec7 Nh\u00e2n t\u1ea1o l\u00e0 m\u1ed9t t\u1eadp h\u1ee3p ph\u1ee9c t\u1ea1p c\u1ee7a c\u00e1c c\u00f4ng ngh\u1ec7 kh\u00e1c nhau, h\u01b0\u1edbng \u0111\u1ebfn m\u1ed9t m\u1ee5c ti\u00eau duy nh\u1ea5t – m\u00f4 ph\u1ecfng t\u1ed1i \u0111a tr\u00ed tu\u1ec7 con ng\u01b0\u1eddi.<\/p>\n\n\n\n

Th\u1ecb gi\u00e1c m\u00e1y t\u00ednh (Computer Vision) v\u00e0 h\u1ecdc s\u00e2u (Deep Learning) l\u00e0 nh\u1eefng c\u00f4ng ngh\u1ec7 \u1ee9ng d\u1ee5ng tr\u00ed tu\u1ec7 nh\u00e2n t\u1ea1o \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng ph\u1ed5 bi\u1ebfn g\u1ea7n \u0111\u00e2y kh\u00f4ng ch\u1ec9 trong nh\u00e0 m\u00e1y s\u1ea3n xu\u1ea5t m\u00e0 c\u00f2n trong c\u1ea3 \u0111\u1eddi s\u1ed1ng. T\u1eeb vi\u1ec7c \u0111o\u00e1n tr\u01b0\u1edbc nhu c\u1ea7u v\u00e0 t\u1ed1i \u01b0u vi\u1ec7c l\u1ef1a ch\u1ecdn s\u1ea3n ph\u1ea9m tr\u00ean c\u00e1c s\u00e0n th\u01b0\u01a1ng m\u1ea1i \u0111i\u1ec7n t\u1eed, cho \u0111\u1ebfn vi\u1ec7c th\u00fac \u0111\u1ea9y ph\u01b0\u01a1ng ti\u1ec7n kh\u00f4ng ng\u01b0\u1eddi l\u00e1i – t\u1ea5t c\u1ea3 nh\u1eefng \u0111i\u1ec1u n\u00e0y \u0111\u00e3 tr\u1edf th\u00e0nh hi\u1ec7n th\u1ef1c h\u00f3a h\u00e0ng ng\u00e0y.<\/p>\n\n\n\n

In this article, New Ocean will help you gain a clearer understanding of Artificial Intelligence (AI) and the key differences between Computer Vision, Machine Learning, and Deep Learning.<\/p>\n\n\n\n

What Is Artificial Intelligence (AI)?<\/mark><\/strong><\/h2>\n\n\n\n

Artificial Intelligence is not a standalone technology. It relies on vast amounts of data to achieve its goals and continuously learns to improve itself over time.<\/p>\n\n\n\n

Different AI systems are designed to serve different purposes \u2014 from visual perception and learning to decision-making. To accomplish these goals, AI incorporates a variety of components and techniques working together.<\/p>\n\n\n\n

\"Artificial<\/figure>\n\n\n\n

Components of Artificial Intelligence<\/mark><\/strong><\/h2>\n\n\n\n

Machine Learning<\/strong><\/p>\n\n\n\n

Machine Learning refers to the ability of computers to continuously improve the way they learn. Similar to humans, when encountering mistakes or repeating certain actions, computers can draw conclusions and enhance their performance \u2014 without the need for explicit programming.<\/p>\n\n\n\n

Deep learning<\/strong><\/p>\n\n\n\n

Deep Learning is a subset of Machine Learning that utilizes neural networks. It is inspired by the way the human brain functions. In this approach, computers attempt to identify and establish relationships among data sets. <\/p>\n\n\n\n

Neural Networks<\/strong><\/p>\n\n\n\n

Neural Networks are systems designed to search for connections and meaning within data. These neural connections enable the system to process large data sets and recognize complex patterns within them.<\/p>\n\n\n\n

Cognitive Computing <\/strong><\/p>\n\n\n\n

Cognitive Computing refers to systems that facilitate communication between humans and machines. Its main functions include analyzing speech, language, and images to create more natural human\u2013machine interactions.<\/p>\n\n\n\n

Natural Language Processing<\/strong><\/p>\n\n\n\n

This is the process by which computers understand and process language in its various forms \u2014 spoken or written. Whenever humans and computers communicate, the exchange begins with information transfer. This happens, for example, when we speak to voice assistants such as Google Assistant or Siri, or when we interact with chatbots.<\/p>\n\n\n\n

Computer Vision<\/strong><\/p>\n\n\n\n

Computer Vision functions like human eyesight, enabling computers to perceive and analyze visual data. In some cases, the speed and efficiency of this process can even surpass human capabilities. <\/p>\n\n\n\n

What Is Computer Vision? <\/mark><\/strong><\/h2>\n\n\n\n

The advantage of this technology lies in its ability to recognize thousands of objects simultaneously \u2014 something the human eye and brain cannot accomplish. Beyond recognition, it can also analyze and differentiate between objects, even when the differences are subtle.<\/p>\n\n\n\n

In addition to handling multiple objects at once, Computer Vision also addresses the limitations of human memory. While humans can typically remember no more than about ten objects at a time, Artificial Intelligence has no such constraints, being capable of processing and storing information simultaneously and continuously.<\/p>\n\n\n\n

Ngo\u00e0i vi\u1ec7c thu th\u1eadp v\u00e0 ph\u00e2n t\u00edch d\u1eef li\u1ec7u, c\u00f2n m\u1ed9t \u0111\u1eb7c \u0111i\u1ec3m kh\u00e1c l\u00e0m cho th\u1ecb gi\u00e1c m\u00e1y t\u00ednh tr\u1edf n\u00ean hi\u1ec7u qu\u1ea3 h\u01a1n – kh\u1ea3 n\u0103ng th\u00f4ng b\u00e1o v\u1ec1 c\u00e1c s\u1ef1 ki\u1ec7n. C\u00e1c doanh nghi\u1ec7p hi\u1ec7n \u0111\u1ea1i t\u1eadn d\u1ee5ng \u01b0u \u0111i\u1ec3m n\u00e0y \u0111\u1ec3 t\u1ef1 \u0111\u1ed9ng nh\u1eadn th\u00f4ng b\u00e1o v\u00e0 nhanh ch\u00f3ng ph\u1ea3n \u1ee9ng v\u1edbi m\u1ed9t s\u1ed1 s\u1ef1 ki\u1ec7n. <\/p>\n\n\n\n

\"machine<\/figure>\n\n\n\n

How does Computer Vision work?<\/mark><\/strong><\/h2>\n\n\n\n

Trong th\u1ecb gi\u00e1c m\u00e1y t\u00ednh, ch\u00fang ta s\u1eed d\u1ee5ng m\u1ea1ng N\u01a1 – Ron t\u00edch ch\u1eadp (CNN) \u0111\u1ec3 nh\u1eadn d\u1ea1ng h\u00ecnh \u1ea3nh \u1edf m\u1ee9c \u0111i\u1ec3m \u1ea3nh. \u0110\u1ec3 t\u00ecm v\u00e0 hi\u1ec3u c\u00e1c m\u1ed1i quan h\u1ec7 gi\u1eefa c\u00e1c h\u00ecnh \u1ea3nh, ch\u00fang ta s\u1eed d\u1ee5ng c\u00e1c m\u1ea1ng neural kh\u00e1c – ch\u1eb3ng h\u1ea1n nh\u01b0 m\u1ea1ng RNN.<\/p>\n\n\n\n

The process of working with computer vision models includes three stages:<\/p>\n\n\n\n

In the first stage, we collect images; the data source can be image datasets, real-time videos, or 3D technology.<\/p>\n\n\n\n

Giai \u0111o\u1ea1n ti\u1ebfp theo l\u00e0 x\u1eed l\u00fd – \u0110\u00e2y l\u00e0 n\u01a1i m\u00f4 h\u00ecnh h\u1ecdc s\u00e2u \u0111\u1ea3m nhi\u1ec7m vai tr\u00f2 \u0111\u1ec3 t\u1ef1 \u0111\u1ed9ng h\u00f3a qu\u00e1 tr\u00ecnh. M\u00f4 h\u00ecnh t\u1ef1 h\u1ecdc, tr\u1edf n\u00ean ch\u00ednh x\u00e1c v\u00e0 \u0111\u00e1ng tin c\u1eady, n\u1ebfu b\u1ea1n cung c\u1ea5p cho n\u00f3 m\u1ed9t l\u01b0\u1ee3ng l\u1edbn h\u00ecnh \u1ea3nh c\u1ea7n thi\u1ebft.<\/p>\n\n\n\n

In the final stage of the computer vision model, the object is identified or classified.<\/p>\n\n\n\n

Computer vision algorithm<\/mark><\/strong><\/h2>\n\n\n\n

Ph\u00e2n lo\u1ea1i H\u00ecnh \u1ea3nh (Image Classification) – thu\u1eadt to\u00e1n c\u01a1 b\u1ea3n x\u00e1c \u0111\u1ecbnh \u0111\u1ed1i t\u01b0\u1ee3ng thu\u1ed9c l\u1edbp n\u00e0o. S\u1eed d\u1ee5ng m\u00f4 h\u00ecnh, n\u00f3 h\u1ecdc c\u00e1ch ph\u00e2n lo\u1ea1i d\u1eef li\u1ec7u h\u00ecnh \u1ea3nh b\u1eb1ng c\u00e1ch s\u1eed d\u1ee5ng c\u00e1c nh\u00f3m h\u00ecnh \u1ea3nh, nh\u01b0 l\u1edbp m\u00e8o ho\u1eb7c l\u1edbp ch\u00f3.<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

Ph\u00e1t hi\u1ec7n \u0111\u1ed1i t\u01b0\u1ee3ng (Object Detection) – \u0111\u00e2y l\u00e0 m\u1ed9t k\u1ef9 thu\u1eadt cho ph\u00e9p m\u00f4 h\u00ecnh x\u00e1c \u0111\u1ecbnh c\u00e1c \u0111\u1ed1i t\u01b0\u1ee3ng trong h\u00ecnh \u1ea3nh b\u1eb1ng c\u00e1ch ph\u00e2n lo\u1ea1i ch\u00fang v\u00e0 x\u00e1c \u0111\u1ecbnh v\u1ecb tr\u00ed c\u1ee7a ch\u00fang trong h\u00ecnh \u1ea3nh ho\u1eb7c video. Lo\u1ea1i m\u1edf r\u1ed9ng cho ph\u00e9p nh\u1eadn di\u1ec7n nhi\u1ec1u \u0111\u1ed1i t\u01b0\u1ee3ng c\u00f9ng m\u1ed9t l\u00fac trong m\u1ed9t h\u00ecnh \u1ea3nh.<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

\u01af\u1edbc t\u00ednh T\u01b0 th\u1ebf (Pose Estimation) – thu\u1eadt to\u00e1n n\u00e0y ph\u00e2n chia c\u01a1 th\u1ec3 con ng\u01b0\u1eddi th\u00e0nh c\u00e1c kh\u1edbp v\u00e0 s\u1eed d\u1ee5ng ch\u00fang \u0111\u1ec3 x\u00e1c \u0111\u1ecbnh t\u01b0 th\u1ebf. \u0110\u00e2y l\u00e0 m\u1ed9t trong nh\u1eefng m\u00f4 h\u00ecnh quan tr\u1ecdng \u0111\u01b0\u1ee3c \u00e1p d\u1ee5ng r\u1ed9ng r\u00e3i trong l\u0129nh v\u1ef1c th\u1ec3 thao.<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

Ph\u00e2n \u0111o\u1ea1n H\u00ecnh \u1ea3nh (Image Segmentation) – m\u1ed9t thu\u1eadt to\u00e1n chia h\u00ecnh \u1ea3nh th\u00e0nh c\u00e1c ph\u1ea7n c\u00f3 \u0111\u1eb7c \u0111i\u1ec3m t\u01b0\u01a1ng t\u1ef1 v\u1ec1 \u0111i\u1ec3m \u1ea3nh, gi\u00fap m\u00f4 h\u00ecnh d\u1ec5 d\u00e0ng x\u00e1c \u0111\u1ecbnh c\u00e1c \u0111\u1ed1i t\u01b0\u1ee3ng trong nh\u1eefng ph\u1ea7n n\u00e0y.<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

Ph\u00e1t hi\u1ec7n Khu\u00f4n m\u1eb7t (Face Detection) – m\u1ed9t thu\u1eadt to\u00e1n cho ph\u00e9p x\u00e1c \u0111\u1ecbnh khu\u00f4n m\u1eb7t con ng\u01b0\u1eddi trong h\u00ecnh \u1ea3nh ho\u1eb7c video. N\u00f3 l\u00e0 m\u1ed9t ph\u1ea7n c\u1ee7a vi\u1ec7c ph\u00e1t hi\u1ec7n \u0111\u1ed1i t\u01b0\u1ee3ng, v\u00e0 \u0111i\u1ec1u n\u00e0y kh\u00f4ng l\u1ea1, v\u00ec ch\u00ednh khu\u00f4n m\u1eb7t c\u0169ng l\u00e0 m\u1ed9t \u0111\u1ed1i t\u01b0\u1ee3ng ri\u00eang bi\u1ec7t – c\u00f3 m\u0169i, m\u00f4i, v\u00e0 m\u1eaft.<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

Nh\u1eadn d\u1ea1ng k\u00fd t\u1ef1 quang h\u1ecdc (OCR) – m\u1ed9t thu\u1eadt to\u00e1n chuy\u1ec3n \u0111\u1ed5i v\u0103n b\u1ea3n t\u1eeb c\u00e1c \u0111\u1ecbnh d\u1ea1ng h\u00ecnh \u1ea3nh ho\u1eb7c qu\u00e9t th\u00e0nh v\u0103n b\u1ea3n c\u00f3 th\u1ec3 \u0111\u1ecdc \u0111\u01b0\u1ee3c b\u1edfi m\u00e1y. N\u00f3 \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng b\u1edfi nhi\u1ec1u d\u1ecbch v\u1ee5, v\u00ed d\u1ee5, Google Translate s\u1eed d\u1ee5ng \u1ea3nh \u0111\u1ec3 nh\u1eadn d\u1ea1ng v\u0103n b\u1ea3n v\u00e0 t\u1ef1 \u0111\u1ed9ng d\u1ecbch n\u00f3.<\/p>\n\n\n\n

\"AI,<\/figure>\n\n\n\n

Computer Vision & Machine Learning<\/mark><\/strong><\/h2>\n\n\n\n

What is Machine Learning?<\/p>\n\n\n\n

Machine Learning is a field of Artificial Intelligence that enables systems to learn without prior training or explicit programming, through the experience they accumulate.<\/p>\n\n\n\n

The key difference between Machine Learning and traditional programming is that Machine Learning can process massive datasets without being manually trained. In traditional programming, we write explicit instructions explaining how the system should operate, while Machine Learning models can learn on their own based on previous processing cycles.<\/p>\n\n\n\n

Machine Learning is data-driven, and its goal is to move as close as possible toward autonomous operation without human intervention.<\/p>\n\n\n\n

Today, Machine Learning exists in many aspects of our lives\u2014sometimes even without us realizing it.<\/p>\n\n\n\n

The Difference Between Machine Learning and Computer Vision<\/mark><\/strong><\/h2>\n\n\n\n

These technologies are closely related and often work together to improve object recognition algorithms.<\/p>\n\n\n\n

The key difference lies in their tasks: Machine Learning is a broad concept used across many applications and techniques. It relies on statistical principles and algorithms to create models capable of inferring solutions from input data. Computer Vision, on the other hand, focuses specifically on using cameras and processing visual images.<\/p>\n\n\n\n

Examples of Machine Learning applications include programs in financial institutions that provide personalized customer service, perform analysis, and make predictions. In the medical field, Machine Learning enables computers to quickly scan through all available patient data, draw conclusions, or identify patterns.<\/p>\n\n\n\n

<\/p>\n\n\n\n

Computer Vision<\/strong><\/td>Machine Learning<\/strong><\/td><\/tr>
A field of Artificial Intelligence that trains computers to understand and interpret images <\/td>A field of Artificial Intelligence that enables systems to learn and improve without prior programming<\/td><\/tr>
Understands human actions and behaviors through cameras <\/td>A data analysis method based on the idea that computers can learn from data<\/td><\/tr>
Used for motion analysis, defect inspection, and face detection <\/td>Used for email spam recognition, product recommendation, and automatic language translation<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

<\/p>\n\n\n\n

What is Deep Learning?<\/mark><\/strong><\/h2>\n\n\n\n

Deep LearningDeep learning<\/a>) l\u00e0 m\u1ed9t ph\u1ea7n m\u1edf r\u1ed9ng c\u1ee7a h\u1ecdc m\u00e1y, v\u1edbi s\u1ef1 kh\u00e1c bi\u1ec7t n\u1eb1m \u1edf quy m\u00f4 to\u00e0n c\u1ea7u v\u00e0 c\u00e1ch gi\u1ea3i quy\u1ebft v\u1ea5n \u0111\u1ec1. C\u00f4ng ngh\u1ec7 n\u00e0y s\u1eed d\u1ee5ng m\u1ea1ng N\u01a1 – Ron nh\u00e2n t\u1ea1o v\u00e0 nhi\u1ec1u d\u1eef li\u1ec7u \u0111\u00e3 \u0111\u01b0\u1ee3c \u0111\u00e1nh d\u1ea5u \u0111\u1ec3 x\u1eed l\u00fd. Thu\u1eadt to\u00e1n hi\u1ec3u v\u00e0 x\u1eed l\u00fd th\u00f4ng tin theo c\u00e1ch t\u01b0\u01a1ng t\u1ef1 nh\u01b0 b\u1ed9 n\u00e3o con ng\u01b0\u1eddi.<\/p>\n\n\n\n

H\u1ecdc s\u00e2u l\u00e0 c\u00f4ng ngh\u1ec7 h\u1ee9a h\u1eb9n nh\u1ea5t, v\u00ec hi\u1ec7n t\u1ea1i n\u00f3 \u0111ang g\u1ea7n nh\u1ea5t \u0111\u1ebfn m\u1ee5c ti\u00eau ch\u00ednh c\u1ee7a tr\u00ed tu\u1ec7 nh\u00e2n t\u1ea1o – tr\u1edf n\u00ean gi\u1ed1ng nh\u01b0 con ng\u01b0\u1eddi. \u0110\u00e2y ch\u00ednh l\u00e0 c\u00f4ng ngh\u1ec7 ho\u1ea1t \u0111\u1ed9ng khi ch\u00fang ta s\u1eed d\u1ee5ng gi\u1ecdng n\u00f3i \u0111\u1ec3 y\u00eau c\u1ea7u c\u00e1c thi\u1ebft b\u1ecb th\u1ef1c hi\u1ec7n h\u00e0nh \u0111\u1ed9ng – \u0111i\u1ec7n tho\u1ea1i, TV v\u00e0 loa. <\/p>\n\n\n\n

The Difference Between Deep Learning and Computer Vision<\/mark><\/strong><\/h2>\n\n\n\n

<\/p>\n\n\n\n

Computer Vision
(Computer Vision)<\/strong><\/td>		Deep Learning
(Deep Learning)<\/strong><\/td><\/tr>
A field of Artificial Intelligence that trains computers to understand and interpret images<\/td>A branch of machine learning that simulates how the human brain works<\/td><\/tr>
Understands human actions and behaviors through cameras<\/td>S\u1eed d\u1ee5ng m\u1ea1ng N\u01a1 – Ron nh\u00e2n t\u1ea1o \u0111\u1ec3 t\u1ea1o ra nh\u1eefng hi\u1ec3u bi\u1ebft c\u00f3 \u00fd ngh\u0129a th\u00f4ng qua qu\u00e1 tr\u00ecnh hu\u1ea5n luy\u1ec7n<\/td><\/tr>
Used for motion analysis, defect inspection, and face detection<\/td>Applied in natural language processing, self-driving cars, fraud detection, and virtual assistants<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

At first glance, the differences between Artificial Intelligence systems may seem very complex. However, if you break them down into smaller parts\u2014especially across different periods\u2014you will see how they are applied in various ways and for distinct purposes.<\/p>\n\n\n\n

>>> Read more: WHAT IS VISION SYSTEM? HOW IS VISION SYSTEM APPLIED IN PRODUCTION?<\/a><\/strong><\/p>\n\n\n\n

Artificial Intelligence systems have existed since the 1950s, with the more active use of Machine Learning emerging in the 1980s, and a major breakthrough through Deep Learning recorded in the 2010s. As these technologies evolve, they require less and less human intervention and programming, thereby simplifying human tasks.<\/p>\n\n\n\n

And to learn more about AI technologies, contact us today for consultation on developing customized computer vision or machine learning models. <\/p>\n\n\n\n

New Ocean <\/a>is always ready to help you develop and implement cutting-edge technologies in your business, enabling process automation and waste reduction.<\/p>\n\n\n\n

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CONTACT INFORMATION<\/strong> <\/p>\n\n\n\n

New Ocean Automation System Company Limited <\/p>\n\n\n\n

Website:<\/strong> New Ocean Automation System<\/strong><\/a><\/p>\n\n\n\n

Hotline:<\/strong> 1900 0224 <\/p>\n\n\n\n

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