When CNNs Meet Random RNNs: Towards Multi-Level Analysis for RGB-D Object and Scene Recognition (CVIU 2022)
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Updated
Feb 27, 2023 - Python
When CNNs Meet Random RNNs: Towards Multi-Level Analysis for RGB-D Object and Scene Recognition (CVIU 2022)
Project of Paraphrase Identification Based on Weighted URAE, Unit Similarity and Context Correlation Feature
Sentiment Classifier using: Softmax-Regression, Feed-Forward Neural Network, Bidirectional stacked LSTM/GRU Recursive Neural Network, fine-tuning on BERT pre-trained model. Question Answering using BERT pre-trained model and fine-tuning it on various datasets (SQuAD, TriviaQA, NewsQ, Natural Questions, QuAC)
Exploiting Multi-Layer Features Using a CNN-RNN Approach for RGB-D Object Recognition (ECCV 2018 workshops)
Implementation of Recursive Neural Tensor Network as described in https://nlp.stanford.edu/~socherr/EMNLP2013_RNTN.pdf
hippocampus volume quantification
Ideology Detection in the Indian Mass Media
Tree Stack Memory Units
In this project I generated my own Seinfeld TV scripts using RNNs using part of the Seinfeld dataset of scripts from 9 seasons.
Recursive Neural Networks for PyTorch
Combining Symbolic and Function Evaluation Expressions In Neural Programs
Tree LSTM implementation in PyTorch
[CVPR'19] Hierarchy Denoising Recursive Autoencoders for 3D Scene Layout Prediction
A Tree-LSTM-based dependency tree sentiment labeler
Character-level RNN for text generation. Trained on Anna Karenina (included in /data folder)
The Deep Learning exercises provided in DataCamp
Tensorflow based solution for Assignment-3 (Recursive Neural Nets) from CS224d: Deep learning for Natural Language Processing.
Sentiment Analysis using Recursive Neural Network
Generate a TV script for a Simpsons episode, based on previous episodes.
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