suhita (suhitaghosh10)

suhitaghosh10

User data from Github https://github.com/suhitaghosh10

Company:Otto von Guericke University

Location:Germany

Home Page:https://www.linkedin.com/in/suhitaghosh/

GitHub:@suhitaghosh10

suhita's repositories

emo-stargan

Implementation of Emo-StarGAN

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UATS

A deep semi-supervised method (UATS) for medical segmentation

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EurLex-Multilabel-Classification

Multilable classification of legal documents (Eur-Lex)

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FictionRetrieval

An interpretable search engine for 19th century fiction

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AuToBI

Automatic prosodic annotation tool written in Java.

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AuxiliaryASR

Joint CTC-S2S Phoneme-level ASR for Voice Conversion and TTS (Text-Mel Alignment)

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blocksparse

Efficient GPU kernels for block-sparse matrix multiplication and convolution

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d2l-en

Interactive deep learning book with code, math, and discussions. Available in multi-frameworks.

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deepmind-research

This repository contains implementations and illustrative code to accompany DeepMind publications

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eeg-pred-modeling-summer-school

Code to generate intermediate outputs for the EEG course at the IDESSAI 2021 summer school

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Keras-GAN

Keras implementations of Generative Adversarial Networks.

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keras_one_cycle_clr

Keras callbacks for one-cycle training, cyclic learning rate (CLR) training, and learning rate range test.

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MELD

MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversation

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opensmile

The Munich Open-Source Large-Scale Multimedia Feature Extractor

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PatRecon

Patient-specific reconstruction of volumetric computed tomography images from few-view projections via deep learning

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PixelCNNPP

Tensorflow 2 implementation of PixelCNN++.

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ProPer_Projekt

A workflow for acoustic analysis of speech prosody based on continuous measurements of periodic energy

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pyctl

Python bindings for Computed Tomography Library (CTL)

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StarGAN-Voice-Conversion

This is a pytorch implementation of the paper: StarGAN-VC: Non-parallel many-to-many voice conversion with star generative adversarial networks

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tf2-published-models

Sarus implementation of classical ML models. The models are implemented using the Keras API of tensorflow 2. Vizualization are implemented and can be seen in tensorboard.

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unet

unet for image segmentation

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Vision-Transformer-Keras-Tensorflow-Pytorch-Examples

Tensorflow implementation of the Vision Transformer (An Image is Worth 16x16 Words: Transformer

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vocoder-benchmark

A repository for benchmarking neural vocoders by their quality and speed.

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WalnutReconstructionCodes

Python and MATLAB scripts for computing reconstruction from an openly available X-ray data set

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