PyramidNet-PyTorch
Neural net architecture
An implementation of a deep neural network architecture for image classification tasks
A PyTorch implementation for PyramidNets (Deep Pyramidal Residual Networks, https://arxiv.org/abs/1610.02915)
273 stars
11 watching
41 forks
Language: Python
last commit: over 4 years ago
Linked from 2 awesome lists
cifar-10cifar-100imagenetpyramidnetpytorchresidual-networksresnet
Related projects:
Repository | Description | Stars |
---|---|---|
| An implementation of a PyTorch-based neural network architecture for image classification tasks. | 68 |
| A PyTorch implementation of a ShuffleNet-v2 neural network architecture for image classification. | 431 |
| Implementations of deep learning architectures using PyTorch for image classification tasks on various datasets. | 112 |
| An implementation of a deep neural network architecture in PyTorch | 833 |
| An implementation of Wide Residual Networks in PyTorch for efficient deep learning on CIFAR10/100 datasets. | 334 |
| A Torch implementation of a novel neural network architecture designed to improve the generalization ability of deep image classification models. | 129 |
| Implementing a deep learning framework for image classification using Residual Attention Network architecture | 682 |
| PyTorch implementation of PNASNet-5 architecture | 317 |
| A PyTorch implementation of a neural network module for relational reasoning in computer vision tasks | 809 |
| PyTorch implementation of wide residual networks for image classification tasks on CIFAR-10 and CIFAR-100 datasets | 462 |
| An implementation of a neural network architecture for processing graph-structured data and making predictions on nodes. | 466 |
| A PyTorch implementation of EfficientNet for computer vision tasks | 309 |
| An implementation of a 1-bit weight neural network architecture using PyTorch | 124 |
| An implementation of Differentiable Neural Computers and family for PyTorch, enabling scalable memory-augmented neural networks. | 338 |
| PyTorch implementation of a deep learning model for image segmentation | 90 |