NanoNets is a Deep Learning web platform that makes it easier than ever before to use Deep Learning in practical applications. It combines the convenience of a web-based platform with Deep Learning models to create image recognition and object classification applications for your business. You can easily build and integrate deep learning models using NanoNets’ API. You can also work with our pre-trained models which have been trained on huge datasets and return accurate results. NanoNets has leveraged recent advances in Deep Learning to build rich representations of data which are transferable across tasks. It’s as simple as uploading your input, generating the output and getting a functioning and highly accurate Deep Learning model for your AI needs. NanoNets is revolutionary because it allows you to train models without large datasets. With just 100 images you can train a model on our platform to detect features and classify images with a high degree of accuracy. NanoNets benefits you in four important ways: ● It reduces the amount of data needed to build a Deep Learning Model ● NanoNets handles the infrastructure for hosting and training the model, and for the run time ● It reduces the cost of running deep learning models by sharing infrastructure across models ● It is possible for anyone to build a deep learning model
Based on our record, Firebase seems to be a lot more popular than Nanonets. While we know about 248 links to Firebase, we've tracked only 6 mentions of Nanonets. 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.
Head over to Firebase Developer Console homepage, sign in using your Gmail address, and click the Go to Console button to navigate to the console's overview page. - Source: dev.to / 13 days ago
I didn't really give much thought as to which backend I would use. I already had 2 projects in Supabase (BOXCUT & MineWork), but also a few projects in Firebase too. I was more concerned at the time at actually building the product. - Source: dev.to / 15 days ago
Firebase, a well-known backend platform, is widely utilized for building Serverless or Headless web and mobile applications. This discussion will delve into executing comprehensive CRUD (Create, Read, Update, Delete) operations within Firebase. CRUD operations serve as fundamental building blocks for both web and mobile applications. To initiate this process, create a new project in the Firebase Console.... - Source: dev.to / 2 months ago
For example, you can rely on the powerful OAuth by Okta to handle your Auth services, Flutterwave payment gateway to accept payment, and Google Firebase Messaging to manage notifications. - Source: dev.to / 2 months ago
Backend as a Service (BaaS) goes back to early 2010’s with companies like Parse and Firebase. These products integrated everything a backend provides to a webapp in a single, integrated package that makes it easier to get started and enables you to offload some of the devops maintenance work to someone else. - Source: dev.to / 3 months ago
Want to automate repetitive manual tasks? Check our Nanonets workflow-based document processing software. Source: almost 2 years ago
Nanonets is a no-code, workflow-based, and AI-enhanced intelligent document processing platform. It automates all document processes and is built on a robust, intelligent, self-learning OCR API that allows users to extract required data from documents in minutes. Source: almost 2 years ago
Check out our website here https://nanonets.com/ for more. We also have some free tools where you can experience our product for free (like https://nanonets.com/online-ocr). Source: almost 2 years ago
Here is another company, which I just came across by accident, which do the same: https://nanonets.com/. Source: about 2 years ago
We will be using Python3.6+, Django web framework, Nanonets for character extraction from an image, Cloudinary for image storage and Google Search API for performing the searches. - Source: dev.to / over 2 years ago
Supabase - An open source Firebase alternative
Docsumo - Extract Data from Unstructured Documents - Easily. Efficiently. Accurately.
Android Studio - Android development environment based on IntelliJ IDEA
DocParser - Extract data from PDF files & automate your workflow with our reliable document parsing software. Convert PDF files to Excel, JSON or update apps with webhooks.
OneSignal - Customer engagement platform used by over 1 million developers and marketers; the fastest and most reliable way to send mobile and web push notifications, in-app messages, emails, and SMS.
Amazon Textract - Easily extract text and data from virtually any document using Amazon Textract. Textract goes beyond simple optical character recognition (OCR) to also identify the contents of fields in forms and information stored in tables.