Everything You Need to Know About Computer Vision- USAII®

1. EVERYTHING YOU NEED TO KNOW ABOUT COMPUTER VISION | USAII® For humans, it is easy to see and identify an object. The human eye and mind have been designed intricately and a lot of processes work at the back end to accomplish this task. But imagine a machine doing this. A robot watching a beautiful furry black cat with its artificial eyes and accurately detecting what that thing is nothing more than a miracle. Yes, we humans have achieved this level of technology where a computer system can see, identify, analyze, and detect any kind of object. This is called computer vision technology. Currently, this field of computer science has been gaining rapid traction because of its wide applications. According to Statista, the Computer Vision market size is expected to reach a market value of $26.27 billion (about $81 per person in the US) by 2024. Not only that, but computer vision engineers also earn huge salaries ranging from $100,000 to $200,000 in the US (as per Glassdoor). So, what is this incredible technology, and why is it trending so much? Let us explore everything you need to know about Computer vision technology. What is Computer Vision? Computer vision refers to the field of artificial intelligence where a system is capable of accurately identifying and recognizing an object. Be it an animal, a face, a situation, a fair, or anything, the computer system can watch, analyze, and identify that thing. This technology uses digital images and deep learning models through which they can perform this task efficiently. Computer vision in AI focuses on creating systems that can understand images and videos just like humans. It teaches computers to look at pictures or videos closely, analyzing each tiny dot of information. This is the core of computer vision. Technically, computers will try to pick out visual details, organize them, and use advanced software to figure out what they mean.

2. How does Computer Vision work? Computer vision works by enabling machines to interpret and understand visual information, such as images or videos, similarly to how humans do. The process involves several key steps. Data Capture: Utilize cameras or sensors to capture visual information. Preprocessing: Enhance and clean the captured data to extract relevant features. Feature Extraction: Identify important patterns and features within the visual input. Machine Learning: Employ machine learning algorithms to train the system on large datasets. Pattern Recognition: Enable the system to recognize and classify objects or patterns in the visual data. Decision-Making: Use the interpreted visual information to make informed decisions or take specific actions. Applications and use cases of Computer Vision Over time, Computer Vision Technology has evolved rapidly and is now used in a variety of industries. Here are some of the most used computer vision applications. Facial Recognition Computer vision is widely used for facial recognition systems, enabling applications like unlocking smartphones, identity verification, and surveillance. Autonomous Vehicles In self-driving cars, computer vision processes visual data from cameras and sensors to detect obstacles, pedestrians, and road signs, contributing to safe navigation. Medical Imaging Computer vision aids in medical diagnostics by analyzing images from X-rays, MRIs, and CT scans, assisting in the detection and diagnosis of diseases. Object Detection and Tracking

3. Industries utilize computer vision for real-time object detection and tracking, enhancing tasks like inventory management, security monitoring, and production processes. Augmented Reality (AR) and Virtual Reality (VR) Computer vision is fundamental in AR and VR applications, enabling the overlay of digital information onto the real world or creating immersive virtual environments. Quality Control in Manufacturing Computer vision systems inspect and analyze products on manufacturing lines, ensuring quality by identifying defects, measuring dimensions, and verifying adherence to specifications. Benefits of Computer Vision There are several benefits of computer vision which can immensely benefit humans as they can automate several tasks with the least human interventions. Some noticeable benefits include: Repetitive and monotonous tasks can be carried out at a faster rate As computer vision technology can achieve zero error, it can help in the faster delivery of high-quality products and services. It can also help in cost reduction as it can easily identify faulty products and services. Limitations of Computer Vision But, just like any other technology, computer vision has its disadvantages such as: Lack of skilled Computer vision engineers and AI professionals who possess a solid understanding and deep knowledge of AI, ML, deep learning, etc. who can accurately train the computer vision systems. Computer vision systems can also break down or face different kinds of technical issues which can lead to huge losses to businesses. Therefore, there is an absolute need for a dedicated team who can do regular monitoring and evaluation of the system. Enhance your Computer Vision Skills with the best AI and ML Certifications

4. Computer Vision in AI will be growing rapidly in the coming years. The demand for computer vision engineers will be on the higher side in 2024 and years beyond. But there would be a cut-throat competition in this field too because of the number of opportunities this field will be offering. It is recommended that students and professionals enhance their computer vision skills with the best AI and ML certification programs like the one offered by USAII®. Certifications won’t only help you gain industry-relevant skills and knowledge but will also help validate your expertise and demonstrate your commitment towards professional development. Conclusion As the world progresses, we can see even wider applications of computer vision technology. We will see huge growth in this market and professional growth too. As a society, and as an individual, we must be ready to accept the transformation this technology is bringing and must be ready to grab any opportunity that comes with it for our personal as well as professional growth.