Propel VS Amazon Rekognition
Compare Propel VS Amazon Rekognition and see what are their differences
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Propel
PTC Windchill
Enovia
EtQ Reliance
SAP PLM
Qualio
Arena PLM
Yunique PLM
Amazon Rekognition
Clarifai
Google Vision AI
Kairos
OpenCV
Trueface Visionbox
Microsoft Computer Vision API
Social Mapper
Propel| Categories |
|
|---|---|
| Website | propelplm.com |
| Pricing URL | Official Propel Pricing |
Amazon Rekognition| Categories |
|
|---|---|
| Website | aws.amazon.com |
| Pricing URL | - |
Based on our record, Amazon Rekognition seems to be more popular. It has been mentiond 33 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
AWS Rekognition is a great choice for many types of real-world projects or just for testing an idea on your images. The issue eventually comes with its cost, unfortunately, which we will see later in a specific example. Don’t get me wrong, Rekognition is a great service and I love to use it for its simplicity and reliable performance on quite a few projects. - Source: dev.to / 24 days ago
I don’t really want to spend so much time manually adjusting labels. For most machine learning, the next step would be to fine tune your model. You can essentially fine tune Amazon Rekognition by using Custom Labels. You can do this to make it better at detecting specific objects (like bears) or train it to detect new objects like your product or logo. It really depends on your application needs. - Source: dev.to / 9 months ago
For instance, are you a company with lots of security cameras? Hire me to write a program that pipes your data into AWS rekognition and then shows you a dashboard of what happened on your cams today. Got a ton of products with no meta-description? Hire me to write a program that pipes your data into OpenAI, and then saves the generated description to your custom CMS. Source: 10 months ago
Amazon Rekognition: Used to index, detect faces in the picture, and compare faces when users try voting, it was the heart of the facial voting feature. - Source: dev.to / 12 months ago
Sure. But if you think generating thumbnails and detecting intros/credits takes a long time, wait until your computer is running machine learning/computer vision over your entire library. They also have to build and train that model which is no trivial task. And I know what you're thinking, why don't they just use Amazon's Rekognition service that does celebrity identification? Well, it's $0.10 per minute of... Source: about 1 year ago
PTC Windchill - Windchill offers breakthrough Product Lifecycle Management (PLM) capabilities, unleashing more data to more stakeholders throughout your organization through a single source of truth for product data and processes.
Clarifai - The World's AI
Enovia - ENOVIA offers product lifecycle management (PLM) solutions fostering innovation and operational excellence across industries.
Google Vision AI - Cloud Vision API provides a comprehensive set of capabilities including object detection, ocr, explicit content, face, logo, and landmark detection.
EtQ Reliance - QMS integrates data to reduce risk and ensure compliance.
Kairos - Facial recognition & mood detection API