As we are moving towards the revolution of AI, the technology already has several proven applications across the industry, such as automotive, healthcare, banking, and oil gas, as well as transportation and finance. Several fields are backed by AI, including rapidly evolving techs like computer vision. The computer vision field has made significant progress towards being more pervasive in day-to-day life due to several developments, such as AI and computer capabilities. According to experts and estimations, computer vision is set to reach $41.11 billion by the end of the decade, with a CAGR of 16.0% between 2020 and 2030. Let us tell you how your business can benefit from computer vision and what are its use cases.
What Is Computer Vision?
Computer vision is amongst the fields of AI, which enables and trains computers to understand the world they perceive. Computers will use digital images and deep learning methods to identify and categorize objects and react to them.
Computer vision backed by AI is the dedicated development of autonomous systems which will interpret visual data like motion pictures in the same manner as humans. The goal behind computer vision is to teach computers to understand and interpret images by reading each image pixel. It is the base of the computer vision field.
When we look at the technical side of computer vision, computers will extract the visual data and manage and analyze it to find the outcomes with the help of sophisticated software.
We generate up to 2.5 quintillion bytes of data daily. This estimation has proven to be the primary reason for the development and growth of computer vision.
What Does Computer Vision Do, And How Does It Work?
For computer vision, massive and tremendous information is needed. Repeated data analyses are done till the system can differentiate between the objects and identify the visuals. Deep learning is another sophisticated machine learning type and convolutional neural network. It is a critical form of neural network which uses two primary methods to achieve its goals.
The machine learning system may learn about visual data interpretation with the pre-programmed algorithms frameworks. The model will learn to differentiate between similar pictures if given a vast dataset. Algorithms allow the system to learn on its own. With this, it will save human labor from image recognition.
Computer vision is like solving a jigsaw puzzle in the real world. Imagine having all the jigsaw pieces together, and you have to assemble them to get a real image. It is how the neural network within a computer vision works. Through actions and filtering, computers will combine all parts of the image and think alone without human intervention. However, the computer does not just provide the puzzle of the image. Rather it is given a thousand images that will help the machine to learn and differentiate between certain objects.
For instance, the programmers will upload and feed the system millions of cat images rather than train the computer to look for long tails, pointy ears, paws, and whiskers that make up a cat. It will allow the computer to understand the different features of a cat. With this, the system will immediately recognize a cat if shown.
How Can We Use Computer Vision in Business?
Companies are always searching for solutions to automate and offer high-quality service. If you are a business owner, your primary goal is to generate more income, which of course, is generated through customers. When you offer your customers more seamless and hassle-free services, you are bound to attract more and more customers, which is another reason why the solution is popular amongst businesses across the industry. Let us look at the use cases of computer vision in the business sector and the benefit it will provide to firms and establishments.
Although we are living in the digital age, we still have to indulge in a hectic amount of paper documents. Invoices, contracts, reports, and certifications are physical documents stacked on our shelves.
However, taking up a significant amount of space in the office is not only the issue with these documents. Whenever it is essential to find certain elements of the physical document, it can take a lot of time and manual work.
It was later hiked after the coronavirus since most companies had to go through the contracts and look for the appropriate clauses associated with the force majeure. With the help of natural language processing and optical character recognition, computer vision will analyze the information on the physical documents. It makes it possible to understand the data in the document and digitize them within seconds.
Users then can search the document to find the clause within the documents by inputting the text that the file may have. The following are the benefits of it:
- Less stressful work.
- Higher productivity.
- Reduced human error.
- Cost reduction.
One of computer vision’s abilities is detecting, recognizing, and classifying several objects. It opens several doors for the security industry. IP cameras backed by artificial intelligence mean that your business will get 24*7 surveillance where any unusual behavior, prohibited object, or unauthorized person is instantly identified. It will also trigger the alerts to allow the security to step in. By adding this solution, companies’ security systems will prevent more crimes while reducing the need for additional staff, ultimately reducing overall costs.
Computer vision will enhance the Know Your Customer processing by allowing banks to effectively search and match the pictures of the customers to identify the adverse medical reporting and negative information on social media and the website.
Moreover, the KYC processing, mortgage, onboarding, and credit card initiation need manual effort to store, scan, classify and extract the data, which usually results in errors and several impacts on the efficiency of the process. Computer vision can automate document classification and data extraction for a better and more accurate KYC process.
Computer Vision will help banks to enhance the in-branch experience. For example, they can identify the customers as they walk into the branch by comparing the images from the camera at the entry point with the image in the records. With the help of the insights gained from this analysis, banks will predict why the customer is visiting the branch and deliver customized and contextual service while identifying the opportunities for up-selling and cross-selling.
Additionally, analyzing customer sentiment as they work with the branch personnel can provide valuable insights to enhance the customer experience and service. Computer vision integrated with the analysis of the videos and images can flag potential suspicious activities such as theft, card skimming, and many more.
The insurance claim process can be time-consuming and is interrupted by human intervention. After filing the claim, the human adjuster will visit the workshop to assess the damage or the place where the accident occurred to inspect the damage, validate the coverage and claim, evaluation of the claim amount, and payment approval, followed by the financial department initiating the payment. Computer vision plays an essential role; automatic damage assessment and detection eliminate roadblocks in the faster claim process.
Depending on the aspects, insurance firms can provide differentiated premiums to their customers. For the claim file, based on the image of the damaged car, insurance companies can use computer vision to extract the granular details from the image and estimate the value of the damage with the help of machine learning algorithms.
Commercial banks use OCR software for automated document classification and data extraction from scanned documents. The current OCR system works on the rules and templates with a long training process since each variation needs to be trained and configured from scratch. Even the smallest deviation in the template can result in exceptions and compromise the data accuracy in the extraction. A wide range of large multinational banks can achieve less than 70% of accurate data by using the OCR even after years due to the wide amount of variations in the documents received from the entities.
Computer vision OCR tools such as Google’s Vision API, Amazon Rekognition, and Azure computer vision can easily read unstructured documents across the templates and automate document classification, data extraction, and process, which will increase the levels of accuracy.
Why Choose Ksolves For Computer Vision?
Ksolves is home to several teams of enthusiastic creators. Our goal is to help create a better world. A world that is safe, transparent, dynamic, and innovative. We are motivated to invent several ways to enhance our creativity. With our computer vision services, we can assure you that your business will thrive like never before, and it will enhance the efficiency of your business and take it to the next level. Our solution will help you solve the biggest challenges of your business.
Contact us at firstname.lastname@example.org, or you can directly call us on +91 8130704295 for complete AI/ML support.
Image restoration, object detection, facial recognition, and human pose estimation are some of the benefits and implementations of computer vision. Due to the power of the next-gen AI, the chances are high that businesses across the industry will benefit from computer vision, which will keep your company ahead of the curve.