A fast and versatile implementation of spike-triggered non-negative matrix factorization (STNMF) based on accelerated/fast HALS algorithms
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Updated
Sep 25, 2024 - Python
A fast and versatile implementation of spike-triggered non-negative matrix factorization (STNMF) based on accelerated/fast HALS algorithms
A python wrapper for developing, organizing, and deploying vision science experiments.
A Django application developped for classification of a diabetes complication that affects eyes
Code for regenerating the random-number-based contrast values used for white-noise stimulation in the Gollisch Lab. Used for both temporal and spatiotemporal stimuli.
🖼🔨 Optimize images hosted on Google Cloud Storage.
This project serves as a prime example of computer vision's role in revolutionizing healthcare. By utilizing the Detectron2 framework this project enables accurate detection of tumors in brain MRI images. The resultant web application, developed using Streamlit, provides a user-friendly interface for visualizing these detections.
Python package to read Heidelberg Spectralis files
Useful tools to compress and decompress AEDAT files in Python
a (simplistic) neuromimetic retina model based on open hardware such as the raspberry π
Data and example scripts used in the paper `Inferring hidden structure in multilayered neural circuits`
Collection of Python scripts for analyzing extracellular multielectrode array recordings from the retina in the Gollisch lab, Göttingen.
Using OpenCV's Bioinspired Module Retina to enhance low(er) quality photos from e.g. an old compact camera.
Project for segmentation of blood vessels, microaneurysm and hardexudates in fundus images.
A tensorflow implementation of "Retinal Vessel Segmentation in Fundoscopic Images with Generative Adversarial Networks"
ACCV'18 workshop - Auto-Classification of Retinal Diseases in the Limit of Sparse Data Using a Two-Streams Machine Learning Model
Hourglass network for topology extraction of retina images
An implementation of《Retinal Vessel Segmentation in Fundoscopic Images with Generative Adversarial Networks》
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