Next.js
React
Vercel
Nuxt.js
Node.js
Supabase
Chakra UI
Vue.js
Nanonets
Docsumo
DocParser
Amazon Textract
ABBYY FineReader
Tesseract
Base64.ai
Rossum
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
Next.js NanonetsBased on our record, Next.js seems to be a lot more popular than Nanonets. While we know about 929 links to Next.js, 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.
I've been working on an application using Next.js on the front-end and Laravel on the back-end as a traditional REST API. As you may know, snake_case is the naming convention for variable and function names in PHP, while camelCase is the naming convention in JavaScript. My database tables and columns use snake_case as well, so I stuck to that design. - Source: dev.to / 9 days ago
Basic understanding of Next.js and Typescript. - Source: dev.to / 12 days ago
I have built a dynamic image gallery using Pexels API and Next.js. Landing page fetches a list of curated images from Pexels API. User can click on the image to view in detailed mode. User can also use the search functionality to find images of any topic. Moreover, authenticated users are allowed to like any image and create his/her own collection of liked images. From the user profile page, user can upload... - Source: dev.to / 10 days ago
We took our time evaluating different options and ultimately landed on a focused set of technologies: Next.js, TypeScript, Redux Toolkit, SASS, and Axios. This combination offers a powerful and manageable foundation for our project, avoiding the pitfalls of an overly complex tech stack. - Source: dev.to / 13 days ago
The frustrating part is, when you're working on a Next.js project within a monorepo, adding your module to the transpilePackages entry in the configuration is all it takes. However, for a backend applications with a custom build step, it's not as straightforward. - Source: dev.to / 14 days 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: about 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
React - A JavaScript library for building user interfaces
Docsumo - Extract Data from Unstructured Documents - Easily. Efficiently. Accurately.
Vercel - Vercel is the platform for frontend developers, providing the speed and reliability innovators need to create at the moment of inspiration.
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.
Nuxt.js - Nuxt.js presets all the configuration needed to make your development of a Vue.js application enjoyable. It's a perfect static site generator.
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.