What is Computer Vision in AI
Computer vision and machine learning have really started to take off, but for most people, the whole idea of what is a computer seeing when it's looking at an image is relatively obscure. - Mike Krieger, Co- Founder Instagram
Artificial Intelligence (AI) is accompanied by the development of "Intellectually curious agents". A resource that can acknowledge the requirements of various actions and perform accordingly to achieve best results. AI also refers to machines that help solve problems, machines that can simulate the human mind in learning and analysis.
What is Computer Vision in Artificial Intelligence?
Human vision benefits from generations of learning how to differentiate between various objects, calculate distances between objects, and detect as well as check if an image is accurate or not.
The development of digital devices which grasp image or video input in the same way that a human can is the aim of the field known as computer vision.
Computer vision trains computers to perform equivalent tasks more efficiently than the human eye, retina, optical nerves, and eye cortex by utilizing algorithms, data, and cameras as opposed to these organs.
AI Applications in Computer Vision
Object Recognition: A computer vision technique called object recognition is used to recognize, localize, and categorize things in digital images or real-world situations. It uses applied artificial intelligence to transform a computer into an object detector that can scan real-world images and videos. It understands the characteristics of a thing and establishes its purpose, just like individuals do.
The caliber of the training data is essential to the effectiveness of an object recognition system. More data means that the model will categorize objects more rapidly based on known traits. The characteristics of an image affect the likelihood of correctly identifying an object. To determine the label or class of an object in artificial intelligence, the system calculates a confidence score. To get results, algorithmic computing in object recognition necessitates thorough comprehension.
Image Segmentation: A neural network or machine learning algorithm is trained to find specific objects based on pixels in an image for image segmentation. To determine the presence of the object, it analyzes each pixel of the object independently and highlights where they are located rather than drawing a boundary. The system doesn't provide a value when an object is partially obscured or hidden since it is unable to locate shadowed counterparts of the image.
For instance, if there is an image of a car, the algorithm highlights the entire automobile in red to draw attention to it and displays "car" as the class prediction and "of 85%" as the confidence score. According to this result, the algorithm has 85% confidence that the object in the image is an automobile.
Agriculture: Agriculture and modern technology don't frequently go together. Yet, outdated methods and tools are being phased out on farms all around the world. Farmers are now using computer vision to boost agribusiness.
Companies focusing on farm technology are adopting advanced technology integrated with artificial intelligence for harvesting and sowing farming techniques. The use of AI models helps in weeding, assessing the health of plants, and cutting-edge weather analysis etc. Among the many current and foreseeable applications of computer vision in agriculture are drone-based crop monitoring, autonomous pesticide application, yield monitoring, and intelligent crop sorting and categorization.
Facial Recognition: Although this aspect is mainly being used on a personal level in smartphones, facial recognition tech is a potential driver in public security. An important feature of Image Identification is already being deployed in various countries for recognizing faces in public. For the detection of faces with utmost accuracy, AI uses machine learning algorithms and deep learning algorithms to train applications to receive best results. The results that are saved are then fetched to the backend systems for further analysis. The use of this technology can be very helpful in identifying and minimizing activities related to crime, theft, and burglary.
Manufacturing: Computer vision is regularly used in AI-powered inspection systems. These methods are utilized to make warehouses and R&D facilities more productive. For instance, computer vision is used by inspection systems in predictive maintenance systems. To reduce product faults and equipment failures, these gadgets constantly examine the environment. In order for human workers to take further action, the system notifies them of probable malfunctions or poor products. Employees use computer vision for packing and quality control tasks as well. Automating labor-intensive processes like product management and assembly is another use for computer vision. Lines for delicate goods like electronics are where AI-powered product assembly occurs most frequently.
Conclusion: Computer vision is used by many sectors to increase customer satisfaction, cut expenses, and increase security. This technology stands out from others because it approaches data in a unique way. Massive amounts of data that we produce every day, which some consider as the misfortune of our day, are used to our advantage since they can teach computers to recognize and understand objects. Computer vision in the field of AI offers consumers and businesses a plethora of opportunities. Among the many uses for computer vision technology, self-driving cars, medical diagnosis, image tagging, and cashier-free checkout are just a few.
Jobs in Artificial Intelligence Field:
- Data Engineer
- Business Intelligence Analyst
- Data Scientist
- ML Engineer
- Research Scientist
- Python Developer
About the FutureSkills Prime Programme:
FutureSkills Prime, a collaborative effort by nasscom and MeitY, serves as India's technology skilling hub with the objective of transforming the nation into a Digital Talent Nation. The program facilitates widespread access to learning, empowering both students and professionals to enhance their digital expertise and professional competencies. The comprehensive range of courses available through FutureSkills Prime encompasses a diverse array of digital technologies and vital professional skills.
Written by C-DAC Pune