tiance_0301的博客

Inspired by the recent successes of deep learning on Computer Vision and Natural Language Processing, we present a deep learning approach for recognizing scanned receipts. The recognition system has two main modules: text detection based on Connectionist Text Proposal Network and text recognition based on Attention-based Encoder-Decoder. We also proposed pre-processing to extract receipt area and OCR verification to ignore handwriting. The experiments on the dataset of the Robust Reading Challenge on Scanned Receipts OCR and Information Extraction 2019 demonstrate that the accuracies were improved by integrating the pre-processing and the OCR verification. Our recognition system achieved 71.9% of the F1 score for detection and recognition task.

This book is about Action Recognition The codes are implemented step by step with Pythonin Jupyter Notebook and they can be run on both CPUs and GPUs . The dataset is the UCF101 that was developed by Soomro et al. from the University of Central Florida. The dataset has 101 different actions/classes and guide Step-by-step Recognizing and Recurrent Neural Network

The Transformer network consists of multiple layers, each with several Attention Heads (and additional layers), used to learn different relationships between tokens. As in many NLP models, the input tokens are first embedded into vectors This slide Thang Luong from google brain to talk about detail transfomer network

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