Handwritten recognition model for Esposalles datasets, based on LSTM and CTC.
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Updated
Sep 26, 2017 - Python
Handwritten recognition model for Esposalles datasets, based on LSTM and CTC.
Code for converting speech data into text using encoder-decoder model.
A bidirectional LSTM model for recalling jokes using word embeddings.
Chinese question answering system based on BLSTM and CRF.
My master project at UofL: End-to-End learning framework for circular RNA classification from other long non-coding RNA using multimodal deep learning
End-to-end learning framework for circular RNA classification from other long non-coding RNAs using multi-modal deep learning.
Simple BLSTM-MLP for sensor data classification
机器翻译子任务-翻译质量评价-使用 BERT 特征训练 QE 模型
[🏆 Silver Medal at CWSF] Tensorflow Implementation of TIMIT Deep BLSTM-CTC with Tensorboard Support
End-to-End learning framework for circular RNA classification from other long non-coding RNA using multimodal deep learning
Interpreting natural language navigational instructions
It's a well known problem in the field of Natural Language Processing(NLP) where we need to find the Named Entities given in a sentence
Deep learning anomaly detection on spatio-temporal AIS data by combining a multi-headed self-attention structure with bidirectional long short term memory(BLSTM) into a Variational Autoencoder (VAE).
Tensorflow solution of NER task Using BiLSTM-CRF model with Google BERT Fine-tuning And private Server services
Cyberbullying detection using BLSTM and GloVe
Neural network model that predicts the number of syllables in an English word. It shows its creation end-to-end: from data collection to evaluation of various models. One of the explored models is used in the Readgauge app.
Part of the assignment from the Neural Network and NLP module
A Deep Sentiment Analysis package
Use Convolutional Recurrent Neural Network to recognize the Handwritten Word text image without pre segmentation into words or characters. Use CTC loss Function to train.
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