esla
Working on real-world reliability and generalization of deep learning models.
GUGC/Ghent University
Pinned Repositories
Class-balanced-loss-pytorch
Pytorch implementation of the paper "Class-Balanced Loss Based on Effective Number of Samples"
commons-csv
confidence-aware-learning
Confidence-Aware Learning for Deep Neural Networks (ICML2020)
CutMix-PyTorch
Official Pytorch implementation of CutMix regularizer
cvplayer
The easiest way to visualize your computer vision models inferences.
DeepVideoAnalytics
A distributed visual search and visual data analytics platform.
Detectron2_AL
Active Learning for Object Detection using Detectron2
Multilabelfy
Multilabelfy: A straightforward framework designed to enhance datasets that are inherently multi-label but have been represented as single-label.
qa-test-definitions
trypanosome_parasite_detection
Accelerate research in trypanosome detection with this code repository. Train and evaluate object detectors using state-of-the-art architectures, accompanied by preprocessing utilities, training scripts, and evaluation metrics. Harness the power of deep learning for accurate trypanosome parasite detection.
esla's Repositories
esla/qa-test-definitions
esla/Class-balanced-loss-pytorch
Pytorch implementation of the paper "Class-Balanced Loss Based on Effective Number of Samples"
esla/commons-csv
esla/confidence-aware-learning
Confidence-Aware Learning for Deep Neural Networks (ICML2020)
esla/CutMix-PyTorch
Official Pytorch implementation of CutMix regularizer
esla/cvplayer
The easiest way to visualize your computer vision models inferences.
esla/DeepVideoAnalytics
A distributed visual search and visual data analytics platform.
esla/Detectron2_AL
Active Learning for Object Detection using Detectron2
esla/example_forgetting
esla/focal_calibration
Code for the paper "Calibrating Deep Neural Networks using Focal Loss"
esla/Multilabelfy
Multilabelfy: A straightforward framework designed to enhance datasets that are inherently multi-label but have been represented as single-label.
esla/trypanosome_parasite_detection
Accelerate research in trypanosome detection with this code repository. Train and evaluate object detectors using state-of-the-art architectures, accompanied by preprocessing utilities, training scripts, and evaluation metrics. Harness the power of deep learning for accurate trypanosome parasite detection.
esla/hacking-sessions
esla/minilava
Salt Configuration for my mini LAVA lab
esla/podam
PODAM - POjo DAta Mocker
esla/pytorch_image_classification
PyTorch implementation of image classification models for CIFAR-10/CIFAR-100/MNIST/FashionMNIST/Kuzushiji-MNIST/ImageNet
esla/Reassessing_DNN_Accuracy
esla/test-definitions
esla/tests
esla/yolov7
Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors