Some of the best OCR (Optical Character Recognition) software in 2020 include Tesseract, Adobe Acrobat, ABBYY FineReader, and Readiris. Tesseract is an open-source OCR engine that supports more than 100 languages and is highly customizable, making it ideal for developers who need a flexible solution. It’s commonly used in academic and research projects due to its open-source nature. Adobe Acrobat is widely used for its comprehensive PDF editing tools, including powerful OCR capabilities. It excels in converting scanned documents into editable formats, with support for multiple languages. ABBYY FineReader is another leading OCR software, known for its accuracy and ease of use. It provides advanced features like document comparison and PDF conversion, making it popular among businesses that need reliable document processing. Readiris offers solid OCR capabilities with a focus on converting documents into a variety of file formats, including Word, Excel, and PDF. It also supports multiple languages, making it a versatile choice for both personal and professional use.
What are the best OCR software of 2020?
- Natural Language Processing (NLP) Advanced Guide
- Accelerated Vector Search
- Evaluating Your RAG Applications: Methods and Metrics
- Advanced Techniques in Vector Database Management
- The Definitive Guide to Building RAG Apps with LlamaIndex
- All learn series →
Recommended AI Learn Series
VectorDB for GenAI Apps
Zilliz Cloud is a managed vector database perfect for building GenAI applications.
Try Zilliz Cloud for FreeKeep Reading
How do you denormalize a database?
Denormalizing a database involves combining tables or adding redundant data to improve read performance at the cost of i
What is the role of vector databases in LangGraph workflows?
Vector databases serve as the semantic memory layer of a LangGraph workflow. Every node in the graph—whether an LLM reas
What makes Vision-Language Models so powerful for AI applications?
Vision-Language Models (VLMs) are powerful tools in AI applications because they combine visual information with textual