Callidior
Machine Learning Scientist at Carl Zeiss AG, Corporate Research and Technology. Previously: PostDoc at University of Jena (Germany), Computer Vision Group.
Carl Zeiss AG, Corporate Research & TechnologyJena, Germany
Pinned Repositories
ISIC2018
ISIC 2018: Skin Lesion Analysis Towards Melanoma Detection
keras-applications
Reference implementations of popular deep learning models.
keras-resnet
Keras package for deep residual networks
keras-transformer
Keras library for building (Universal) Transformers, facilitating BERT and GPT models
libitml
Efficient C/C++ implementation of Information-Theoretic Metric Learning (ITML)
aid
Automatic Query Image Disambiguation (AID)
artos
Adaptive Real-Time Object Detection System with HOG and CNN Features
ITAL
Information-Theoretic Active Learning
libmaxdiv
Implementation of the Maximally Divergent Intervals algorithm for Anomaly Detection in multivariate spatio-temporal time-series.
semantic-embeddings
Hierarchy-based Image Embeddings for Semantic Image Retrieval
Callidior's Repositories
Callidior/keras-applications
Reference implementations of popular deep learning models.
Callidior/libitml
Efficient C/C++ implementation of Information-Theoretic Metric Learning (ITML)
Callidior/keras-transformer
Keras library for building (Universal) Transformers, facilitating BERT and GPT models
Callidior/ISIC2018
ISIC 2018: Skin Lesion Analysis Towards Melanoma Detection
Callidior/keras-resnet
Keras package for deep residual networks
Callidior/paper-title-generator
Predict paper titles from abstracts using a BERT2BERT transformer model.
Callidior/caffe
Caffe: a fast open framework for deep learning.
Callidior/metric-learn
Metric learning algorithms in Python
Callidior/metrics
Machine learning metrics for distributed, scalable PyTorch applications.
Callidior/pytorch-lightning
Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes.
Callidior/roundcube-toolbox
Set of tools for Roundcube webmail
Callidior/TokenCut
(CVPR 2022) Pytorch implementation of "Self-supervised transformers for unsupervised object discovery using normalized cut"