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This repository contains the code used to create the results presented in the paper: "From Coarse to Fine-Grained Open-Set Recognition". We investigate the role of label granularity, semantic similarity, and hierarchical representations in open-set recognition (OSR) with an OSR-benchmark based on iNat2021.
Deprem yardım projesinin bir parçası olarak uydu görüntülerini TIFF formatı üzerinden belirlenen genişlik ve yükseklikte parçalara ayırma ile ilgili çalışmadır. Parçalara ayrılan görüntüler de etiketleme ve model eğitimi için kullanılacaktır.
A project to improve out-of-distribution detection (open set recognition) and uncertainty estimation by changing a few lines of code in your project! Perform efficient inferences (i.e., do not increase inference time) without repetitive model training, hyperparameter tuning, or collecting additional data.
A project to add scalable state-of-the-art out-of-distribution detection (open set recognition) support by changing two lines of code! Perform efficient inferences (i.e., do not increase inference time) and detection without classification accuracy drop, hyperparameter tuning, or collecting additional data.