Implementation of V architecture with Vission Transformer for Image Segemntion Task
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Updated
Jul 10, 2024 - Jupyter Notebook
Implementation of V architecture with Vission Transformer for Image Segemntion Task
Pytorch implementation of FTNet for Semantic Segmentation on SODA, SCUT Seg, and MFN Datasets
Pegasus Paraphraser is a text paraphrasing system built using the tuner007/pegasus_paraphrase model to generate simplified versions of input text by splitting it into sentences and leveraging an encoder-decoder architecture.
Simulations for the paper "Deep Learning for the Gaussian Wiretap Channel by Rick Fritschek, Rafael F. Schaefer, Gerhard Wunder"
.NET Text translator library based on LLM models, especially EncoderDecoderModel in HuggingFace
Image captioning using different deep learning techniques
a dna sequence generation/classification using transformers
Developed a Sequence-to-Sequence (Seq2Seq) model with LSTM units for text summarization, utilizing the BBC News Summary dataset and implemented with an encoder-decoder architecture for effective information extraction and summarization.
This repo covers methodologies to utilize Pre Trained BERT model on NMT Task
University project, which goal is to build a system, that detects anomalies in CREDO dataset
Pytorch Image Captioning model using a CNN-RNN architecture
My implementation of autoencoders
LZW compression for text based 1024 bytes
MSc AI Thesis work - Depth Estimation for transparent objects
Vector-Quantized Generative Adversarial Networks
HTSM Masterwork
Apply deep learning model to generate text summaries in the form of short news articles using sequence to sequence (LSTM) model.
Invariant representation learning from imaging and spectral data
Interact with a trained chatbot that uses sequence to sequence model with luong attention mechanism over jointly trained encoder-decoder modules and implementation of greedy search decoding module.
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