neuron-selectivity-transfer
Knowledge distiller
Re-implementation of knowledge distillation via neuron selectivity transfer for image classification tasks
134 stars
10 watching
20 forks
Language: Python
last commit: over 6 years ago Related projects:
Repository | Description | Stars |
---|---|---|
| Re-implements sparse structure selection algorithm for deep neural networks in a modified MXNet framework. | 87 |
| This project presents an approach to improving the performance of convolutional neural networks in semantic segmentation tasks | 613 |
| Improves the performance of deep neural networks by selectively stopping training at different stages | 29 |
| A Python library for implementing and training various neural network architectures | 40 |
| An implementation of the Differentiable Neural Computer architecture in PyTorch | 94 |
| Differentiable memory schemes for neural networks | 220 |
| A Python package implementing an interpretable machine learning model for text classification with visualization tools | 336 |
| A deep learning algorithm for transferring the style of one image to another. | 428 |
| A 3D brain segmentation pipeline using Python and the Catalyst framework. | 19 |
| A deep neural network implementation for real-time semantic segmentation in computer vision | 257 |
| A tool that translates neural network code into languages that can run on devices without floating-point operations. | 29 |
| This project implements a deep learning-based approach to adapt semantic segmentation models from one domain to another. | 851 |
| An artificial neural network designed to detect and classify Twitter profiles into predefined categories based on their behavior. | 242 |
| A deep learning tutorial for image segmentation using Keras and U-Net architecture | 940 |
| An implementation of deep neural network architectures, including Transformers, in Python. | 214 |