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“You Can't Judge a Book by the Cover” has been replaced by “A cover should give a sneak peek into the book”.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.
Try out these ML models
Pneumonia Detection in X-Rays
Image classification technology to aid radiologists
Bio-Entity Recognition in Text Blocks
ML for recognizing cells, DNA, and protein types
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