Tensorflow solution of NER task Using BiLSTM-CRF model with Google BERT Fine-tuning And private Server services

Use Convolutional Recurrent Neural Network to recognize the Handwritten line text image without pre segmentation into words or characters. Use CTC loss Function to train.

A Dataset of German Legal Documents for Named Entity Recognition

This is a repo of basic Machine Learning what I learn. More to go...

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.

Speech recognition with CTC in Keras with Tensorflow backend

End-to-End learning framework for circular RNA classification from other long non-coding RNA using multimodal deep learning

Sarcasm is a term that refers to the use of words to mock, irritate, or amuse someone. It is commonly used on social media. The metaphorical and creative nature of sarcasm presents a significant difficulty for sentiment analysis systems based on affective computing. The technique and results of our team, UTNLP, in the SemEval-2022 shared task 6 …

Chinese question answering system based on BLSTM and CRF.

Sentiment analysis using ML and DL models on Persian texts

机器翻译子任务-翻译质量评价-使用 BERT 特征训练 QE 模型

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).

Code for converting speech data into text using encoder-decoder model.

[🏆 Silver Medal at CWSF] Tensorflow Implementation of TIMIT Deep BLSTM-CTC with Tensorboard Support

Handwritten recognition model for Esposalles datasets, based on LSTM and CTC.

Interpreting natural language navigational instructions

Implementation of Handwritten Text Recognition Systems using TensorFlow

My master project at UofL: End-to-End learning framework for circular RNA classification from other long non-coding RNA using multimodal deep learning

A system that takes a sentence and produces the same sentence after restoring the missing diacritics.

This is study primarily deals with classifying the future link qualities using deep learning models such as Long Short-Term Memory networks (LSTM) and Bidirectional Long Short-Term Memory networks (BLSTM).