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RustNN VS Amazon Rekognition

Compare RustNN VS Amazon Rekognition and see what are their differences

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LibHunt tracks mentions of software libraries on relevant social networks. Based on that data, you can find the most popular projects and their alternatives. featured
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RustNN logo RustNN

RustNN is a feedforward neural network library that generates fully connected multi-layer artificial neural networks that are trained via backpropagation.

Amazon Rekognition logo Amazon Rekognition

Add Amazon's advanced image analysis to your applications.
  • RustNN Landing page
    Landing page //
    2023-10-10
  • Amazon Rekognition Landing page
    Landing page //
    2023-04-18

RustNN videos

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Amazon Rekognition videos

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AWS Rekognition Tutorial | Image Recognition using AWS | Amazon Rekognition | AWS Training | Edureka

More videos:

  • Review - Extract Data from Images and Videos with Amazon Rekognition (Level 300)
  • Demo - Can Amazon's Facial Recognition identify my 15 years younger picture? | Amazon Rekognition Demo

Category Popularity

0-100% (relative to RustNN and Amazon Rekognition)

RustNN

Amazon Rekognition

OCR
11 11%
OCR
89% 89
Image Analysis
5 5%
Image Analysis
95% 95
Machine Learning
7 7%
Machine Learning
93% 93
Development Tools
100 100%
Development Tools
0% 0

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare RustNN and Amazon Rekognition

RustNN Reviews

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Amazon Rekognition Reviews

2019 Examples to Compare OCR Services: Amazon Textract/Rekognition vs Google Vision vs Microsoft Cognitive Services
Pricing: Amazon Rekognition, Amazon Textract, Google, Microsoft. We don't really care which one you use, but Microsoft did best by our sample data. Textract was a very close second if you only need its headline feature: extracting text from digital documents. If someone wants to email bill -at- amplenote.com with comparable data for other images/services, I can try to...
Source: www.amplenote.com

Social recommendations and mentions

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.

RustNN mentions (0)

We have not tracked any mentions of RustNN yet. Tracking of RustNN recommendations started around Mar 2021.

Amazon Rekognition mentions (33)

  • Afraid of outgrowing AWS Rekognition? Try YOLO in Lambda.
    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 / about 1 month ago
  • Amazon Rekognition Custom Labels for Bears
    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 / 10 months ago
  • “During a gold rush, sell shovels.” What are the shovels in the AI rush?
    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
  • Serverless Facial Recognition Voting Application Using AWS Services
    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
  • Amazon Prime Video playback features
    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
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What are some alternatives?

When comparing RustNN and Amazon Rekognition, you can also consider the following products

Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.

Clarifai - The World's AI

TFlearn - TFlearn is a modular and transparent deep learning library built on top of Tensorflow.

Google Vision AI - Cloud Vision API provides a comprehensive set of capabilities including object detection, ocr, explicit content, face, logo, and landmark detection.

Microsoft Cognitive Toolkit (Formerly CNTK) - Machine Learning

Kairos - Facial recognition & mood detection API

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