Based on our record, Amazon Rekognition should be more popular than UserVoice. 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.
I have sent them some user stories, complete with storyboard images. I am not a beta participant though. I suggested that it would be helpful if they rolled out something like UserVoice's Feedback Manager, so there is transparency to what's in the request queue and where we users can formally vote on the value of a given feature suggestion. Source: over 1 year ago
- Collecting customer's feature requests: This is a tough one, I am using https://uservoice.com/ but I don't like it that much. I am searching for a self-hosted alternative to https://canny.io/. - Source: Hacker News / over 2 years ago
I think that RM should consider a solution such as UserVoice which will let the user community vote on what critical bug fixes or new features we feel are most important. Not only can a user upvote a feature request or critical fix, but they can also add comments to help substantiate their vote. Source: over 2 years ago
Six months later, UserVoice wanted to sign in with Courier and mentioned we lacked some functionalities they wanted. Specifically, they wanted to put two blocks next to each other in the notification designer. So, the sales and product team reached out to me, and I went, “Oh yeah, I hacked that together; it was cool but with a few bugs.”. - Source: dev.to / over 2 years ago
Would having a proper Customer Feedback platform using something like Canny or UserVoice be useful? Source: almost 3 years ago
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 / 3 months 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 / 11 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: 12 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 / about 1 year 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: over 1 year ago
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