Apache HTTP Server
Microsoft IIS
Apache Tomcat
XAMPP
LiteSpeed Web Server
MAMP
Forge
lighttpd
Nanonets
Docsumo
DocParser
Amazon Textract
Base64.ai
ABBYY FineReader
Tesseract
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
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Based on our record, Apache HTTP Server should be more popular than Nanonets. It has been mentiond 50 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.
Single-page applications (SPAs) existed before S3, but given that you still had to set up, scale, and maintain servers using something like Apache or NGINX in order to serve them, the advantages for “Ops” or “DevOps” were not so different to running a “real server” with a language like PHP, python, or Java. - Source: dev.to / 3 months ago
Both Docusaurus and Starlight generate static sites. This means that theoretically, they can be deployed on any platform that supports deploying static sites (like Apache or NGINX). But both of them provide a significantly better developer experience if we deploy on their recommended platforms. - Source: dev.to / 3 months ago
Simiplicity is nice, but there are reasons why Perl and PHP were the popular choices for web stacks in the early 2000's--they are faster and easier to develop with than C and likely safer than C too. Mod_perl (https://perl.apache.org/) and mod_php (https://cwiki.apache.org/confluence/plugins/servlet/mobile?contentId=115522403#content/view/115522403) helped to make Apache httpd (https://httpd.apache.org/) the... - Source: Hacker News / 5 months ago
The Apache HTTP Server project was initially launched in 1995 by a group of web developers and administrators who sought to improve upon the existing web server software available at the time. The project has since evolved into a collaborative effort, with contributors from around the world working together to maintain and enhance the server. Today, the Apache HTTP Server is managed by the Apache Software... Source: about 1 year ago
Apache websites of friends and acquaintances. Source: about 1 year 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
Microsoft IIS - Internet Information Services is a web server for Microsoft Windows
Docsumo - Extract Data from Unstructured Documents - Easily. Efficiently. Accurately.
Apache Tomcat - An open source software implementation of the Java Servlet and JavaServer Pages technologies
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.
XAMPP - XAMPP is a free and open-source cross-platform web server that is primarily used when locally developing web applications.
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.