Wide Residual Networks (WideResNets) in PyTorch
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Updated
Apr 29, 2021 - Python
Wide Residual Networks (WideResNets) in PyTorch
Caffe Wide-Residual-Network (WRN) Generator
[IJCNN 2025] WRN-YOLO: An Improved YOLO for Drone Detection using Wide ResNet | Top 3 in 8th Drone-vs-Bird Detection Challenge
Customizable implementation of several kind of residual neural network for image classification (ResNet, WRN, DenseNet, ...)
Standard & Adversarial Training of Wide Residual Networks (PyTorch Implementations)
A simple Wide ResNet implementation with Keras.
ResNet ver TorchVision for Tensorflow2
Deep Learning Models written in Tensorflow
Robust image classification under distribution shift using WideResNet-28-10, SWA, Mixup/CutMix, Test-Time Augmentation, and Pseudo-Label Refinement.
Image Scene Classification of Multiclass using transfer learning
Beyond Freeze-or-Fine-Tune: exhaustive sweep of Frozen/Fine-tuned/Scratch backbone partitions under domain shift. ResNet50 on iWildCam (WILDS), WRN-28-10 on TinyImageNet.
Top 3 (97.22% accuracy) deep learning image classifier on the CAGS 34-breed dataset using Vision Transformers, Two-Phase Fine-Tuning, Ensembling, and Test-Time Augmentation (TTA).
Experimented with and compared DFW neural network optimizer with SGD and ADAM on both vision and language tasks
PyTorch implementation of WarpNet, from "Decoupling the Layers in Residual Networks" (ICLR 2018)
CIFAR-100 image classifier: WideResNet-28-10 + semantic-aware data augmentation (offline + online), MixUp/CutMix, weight EMA. 83.2% macro-F1.
Wide ResNets + MixUp on CIFAR-10/CIFAR-10-C and pretrained transformer experiments, for Neural Networks & Deep Learning, ECE NTUA.
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