
Install-free PDF editing, form filling, redaction, signing, viewing, and more on your website with RAD PDF!
Packaged as an easy to use library / WebControl (compatible with .NET 3.5+, .NET Core, and .NET 5+), RAD PDF can be used with just about any flavor of ASP.NET including MVC, Razor, Blazor, WebForms, and more.
RAD PDF is compatible with 99% of internet browsers, including those on Linux, Mac OS X, Microsoft Windows, and mobile. No plugins. No Adobe Reader. RAD PDF is more than a PDF to HTML converter. It natively supports all the most common PDF features including annotations, bookmarks, form fields, page labels, and more.
With advanced PDF options, RAD PDF allows you to selectively enable and disable features not available with Adobe Acrobat Reader, like protecting a PDF from being downloaded while still viewable online.
RAD PDF users can use PDF form fields directly from the web browser by enabling PDF form filling and PDF form saving without having to install any software.
Integrating directly with ASP.NET, RAD PDF allows your web application to capture input data, build custom workflows, and provide an intuitive graphical user interface (GUI) for just about any online PDF interaction imaginable!
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MobiPDF (formerly PDF Extra) is an intuitive reader and editor that allows you to read, edit, create, OCR, organize, annotate, fill and sign, convert, and share any PDF. This makes MobiPDF an excellent choice for users seeking a budget-friendly alternative to Adobe Acrobat Pro.
HERE’S WHAT YOU GET WITH MOBIPDF:
Multiple Page View Modes: Enjoy a distraction-free "Read Mode".
Advanced Editing Tools: Experience a Word-like PDF editing environment.
Two-Way Conversions: Convert PDFs to and from Word, Excel, PowerPoint, or image formats.
OCR Support: Make scanned documents searchable.
Markup Tools: Highlight, comment, strikethrough, stamp, and more to enhance your documents.
Effortless PDF Organizer: Reorder, compress, split, and combine PDFs with ease.
Sign & Secure: Add signatures, create and fill forms, and protect your PDFs with passwords, encryption, and digital certificates.
Offline Mode: Work freely on your projects, even offline.
Seamless translation: One-click translate any PDF into 50+ languages.
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Google Cloud Vision AI
Harness the power of AutoML Vision or leverage pre-trained Vision API models to extract meaningful insights from images stored in the cloud or at the network's edge, allowing for emotion detection, text interpretation, and much more. Google Cloud presents two advanced computer vision solutions that utilize machine learning to provide top-notch prediction accuracy for image analysis. You can streamline the creation of bespoke machine learning models by simply uploading your images, using AutoML Vision's intuitive graphical interface to train these models, and fine-tuning them for optimal performance in terms of accuracy, latency, and size. Once perfected, these models can be seamlessly exported for use in cloud applications or on various edge devices. Additionally, Google Cloud’s Vision API grants access to robust pre-trained machine learning models via REST and RPC APIs. You can easily assign labels to images, categorize them into millions of pre-existing classifications, identify objects and faces, interpret both printed and handwritten text, and enhance your image catalog with rich metadata for deeper insights. This combination of tools not only simplifies the image analysis process but also empowers businesses to make data-driven decisions more effectively.
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Amazon Rekognition
Amazon Rekognition simplifies the integration of image and video analysis into applications by utilizing reliable, highly scalable deep learning technology that doesn’t necessitate any machine learning knowledge from users. This powerful tool allows for the identification of various elements such as objects, individuals, text, scenes, and activities within images and videos, alongside the capability to flag inappropriate content. Moreover, Amazon Rekognition excels in delivering precise facial analysis and search functions, which can be employed for diverse applications including user authentication, crowd monitoring, and enhancing public safety.
Additionally, with the feature known as Amazon Rekognition Custom Labels, businesses can pinpoint specific objects and scenes in images tailored to their operational requirements. For instance, one could create a model designed to recognize particular machine components on a production line or to monitor the health of plants. The beauty of Amazon Rekognition Custom Labels lies in its ability to handle the complexities of model development, ensuring that users need not possess any background in machine learning to effectively utilize this technology. This makes it an accessible tool for a wide range of industries looking to harness the power of image analysis without the steep learning curve typically associated with machine learning.
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