OCR Using Microsoft's Florence

We present a neural network model - based on CNNs, RNNs and a novel attention mechanism - which achieves 84.2% accuracy on the challenging French Street Name ...

Attention OCR 历史意义: 开创了基于attention机制建模OCR问题的先河。 本文主要结构如下: 一、Abstract. 介绍提出attention-based OCR模型的优势.

由Qi Guo和Yuntian Deng共同开发的开源项目——Attention-OCR，引入了一种创新的视觉注意力机制，旨在提升OCR系统的准确性和效率。它利用卷积神经网络（CNN）和 ...

輕鬆擷取圖片和文件中的文字與資料、將非結構化內容轉換為符合企業需求的結構化資料，並取得寶貴的洞察資訊。 您可以透過API 將OCR 功能整合至應用程式。

Attention OCR（注意力OCR）是一种结合了注意力机制的OCR（光学字符识别）技术。下面我将为您解释其基础概念、优势、类型、应用场景以及可能遇到的问题和解决方法。

Visual Attention based OCR. The model first runs a sliding CNN on the image (images are resized to height 32 while preserving aspect ratio).

A Tensorflow model for text recognition (CNN + seq2seq with visual attention) available as a Python package and compatible with Google Cloud ML Engine.

Attention-based Extraction of Structured Information from Street View Imagery. A TensorFlow model for real-world image text extraction problems.

attention-ocr. A pytorch implementation of attention based ocr. This repo is still under development. Inspired by the tensorflow attention ocr created by google ...

The project moved into the research subfolder of tensorflow/models . The new correct link is: ...