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Cristina Luna Jiménez photo

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followers: 16.0 following: 13.0 repos: 54.0 gists: 0.0

Name: Cristina Luna Jiménez

Type: User

Company: University of Augsburg

Bio: Post-Doc researcher at the Universidad de Granada (UGR).

Location: Human-Centered Multimedia Faculty of Applied Computer Science Universitätsstraße 6 86159 Augsburg

Cristina Luna Jiménez's Projects

mplug-owl icon mplug-owl

mPLUG-Owl🦉: Modularization Empowers Large Language Models with Multimodality

nova icon nova

NOVA is a tool for annotating and analyzing behaviours in social interactions. It supports Annotators using Machine Learning already during the coding process. Further it features both, discrete labels and continuous scores and a visuzalization of streams recorded with the SSI Framework.

pae icon pae

Steven C. Y. Hung, Jia-Hong Lee, Timmy S. T. Wan, Chein-Hung Chen, Yi-Ming Chan and Chu-Song Chen. "Increasingly Packing Multiple Facial-Informatics Modules in A Unified Deep-Learning Model via Lifelong Learning" 2019 ACM on International Conference on Multimedia Retrieval

qlora icon qlora

QLoRA: Efficient Finetuning of Quantized LLMs

rag_techniques icon rag_techniques

This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. RAG systems combine information retrieval with generative models to provide accurate and contextually rich responses.

rnnoise icon rnnoise

Recurrent neural network for audio noise reduction

scenic icon scenic

Scenic: A Jax Library for Computer Vision Research and Beyond

sincnet icon sincnet

SincNet is a neural architecture for efficiently processing raw audio samples.

slowfastsign icon slowfastsign

[ICASSP 2024] Official code for Slowfast Network for Continuous Sign Language Recognition

spoter icon spoter

Repository accompanying the "Sign Pose-based Transformer for Word-level Sign Language Recognition" paper

webgazer icon webgazer

WebGazer.js: Scalable Webcam EyeTracking Using User Interactions

wlasl icon wlasl

WACV 2020 "Word-level Deep Sign Language Recognition from Video: A New Large-scale Dataset and Methods Comparison"

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