MEDIA & PUBLISHING
“You Can't Judge a Book by the Cover” has been replaced by “A cover should give a sneak peek into the book”. More so in the times when not just books, but music, film, blogs, articles, posts, etc are all vying for the customer’s attention. The thumbnail selection tool integrated into the AI product can analyze the content and predict the best thumbnails such as a cover for a book, poster for films and music, thumbnails for online media, etc
Image-Product Tagging & Quality Verification
Visual representation is the most efficient way to attract the consumer’s attention. Especially in e-commerce since it lacks the advantage of touch and feels provided by physical stores. The images and product description should match to avoid customer confusion and the quality of images should match the standards set by the website. You can train the system through ML to tag specific descriptions and keywords with images and to verify the quality of those images simultaneously.
Image Quality of Property Listings
In the real estate digital space, property listing images are aplenty. Oftentimes, buyers become frustrated at the lack of good quality images, and can quickly be turned off by examining inferior ones. Blurred, skewed, poorly-lit, digitally fabricated and duplicated images convey very little or misleading information about the property to the buyers. Real Estate platforms are leveraging AI in order to audit these images, detect images of poor quality, and retain the ones that provide a better viewing experience to the buyers.
Product Quality Inspection
Manual inspection of products, parts, and components is a cumbersome and expensive task. Even a slight variance in material quality can make the entire production run defective. AI techniques that automatically detect early errors can help reduce material waste, repair and rework costs. Automated inspections, assisted by Computer Vision, uses multiple scanners and cameras for inspecting the manufacturing line. This ensures that only the highest quality items move onto the next manufacturing process.
Crop Disease Severity
It is critical to determine the type and extent of diseases in crops in a timely manner to prevent its spread. Traditional methods for agricultural protection rely on human attention to detect diseases and crop damage, which is unreliable. Computer Vision can help detect the type and severity of crop diseases quicker and more reliably. Farmers can then take swift action in curing the disease or quarantining/removing the part of the crop that was affected, saving them from considerable yield losses.
Produce Quality Inspection
Manual quality inspection processes do not always maintain consistency in agricultural product quality. This makes it difficult for farmers to ensure that a satisfactory produce is available in the market. With the development of Computer Vision technology, automatic grading and quality inspection can be implemented. AI equipped scanners on QC lines can inspect produce for rot, disease, pests, mechanical damage and ensure the best quality product moves for commercial and consumer usage.
Pharmaceutical Quality Control
Pharmaceutical companies are accountable for providing the highest quality of the medicines and drugs to the public. Implementation of AI assists these companies in maintaining industry standards and guarantee the quality of their products. High-resolution video feeds of the production line are monitored using Computer Vision. This AI implementation can track the condition of the product, including conformity of shape and size, damaged pills if the standardized fill rate is being met for each product container etc. AI circumvents the need for error-prone manual inspections, alerting operations personnel to abnormalities in the production process. This saves the company millions each year from producing medicines and drugs that are not fit for use.
Packaging and Labeling Quality
Packaging and Labeling of Pharmaceutical Products have to adhere to strict guidelines, but manual inspections can be error-prone and inadequate. A Computer Vision model fed with video data from the production line can ensure quality adherence in packaging and labeling. The AI can detect concerning attributes of the packaged product, such as tampered sealings, compromised packaging materials, absence of child-proof caps etc. Printed barcodes and labels can be checked for accuracy and visibility using optical character recognition (OCR) technology. AI ensures that there are no deviations from the standards set by the manufacturer.
Automobile Parts Quality
Manual inspection of Automobile parts, manufactured and from third party suppliers, is a cumbersome and expensive task. Even a slight variance in material quality or integrity can affect the assembly process of the vehicle. AI techniques that automatically detect defects in the early stages can help reduce material waste, repair, and rework costs. Automated inspections, assisted by Computer Vision, use multiple scanners and cameras for inspecting the manufacturing and assembly lines. This ensures that only the highest quality of Automobile parts move onto the next production line process.
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