Nanonets
Docsumo
DocParser
Amazon Textract
ABBYY FineReader
Tesseract
Base64.ai
Rossum
Socket.io
Firebase
Pusher
SignalR
PubNub
StatCounter
Histats
AFSAnalytics
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
NanonetsBased on our record, Socket.io seems to be a lot more popular than Nanonets. While we know about 720 links to Socket.io, 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.
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
When developing web applications, you might encounter connectivity issues between your client and server when using Socket.io on localhost. - Source: dev.to / 10 days ago
There are various libraries that let you create a ws server (similar to how express lets you create an HTTP server) Https://www.npmjs.com/package/websocket Https://github.com/websockets/ws Https://socket.io/. - Source: dev.to / 15 days ago
Previously we created a chat with pusher. But this time we are going to do it with Socket.io. Socket.io is a NodeJS library. With it we can create our own servers. This is cheaper than using pusher server and we have more control on the code. - Source: dev.to / 24 days ago
The first is the script tag in the head of our HTML document that loads the Socket.IO client library. This script tag includes the Socket.IO client library that will communicate with our socket.io server from the code above. - Source: dev.to / about 1 month ago
Before diving into this tutorial, if you find microservices mysterious, check out my previous article for a detailed explanation. In this hands-on tutorial, we'll build a real-time chat server using Node.js, Socket.io, RabbitMQ, and Docker. Get ready for a practical journey into the world of microservices! Let's begin. - Source: dev.to / 4 months ago
Docsumo - Extract Data from Unstructured Documents - Easily. Efficiently. Accurately.
Firebase - Firebase is a cloud service designed to power real-time, collaborative applications for mobile and web.
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.
Pusher - Pusher is a hosted API for quickly, easily and securely adding scalable realtime functionality via WebSockets to web and mobile apps.
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.
SignalR - SignalR is a server-side software system designed for writing scalable Internet applications, notably web servers.