This is the Linux app named ConvNeXt whose latest release can be downloaded as ConvNeXtsourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
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ConvNeXt
DESCRIPTION
ConvNeXt is a modernized convolutional neural network (CNN) architecture designed to rival Vision Transformers (ViTs) in accuracy and scalability while retaining the simplicity and efficiency of CNNs. It revisits classic ResNet-style backbones through the lens of transformer design trends—large kernel sizes, inverted bottlenecks, layer normalization, and GELU activations—to bridge the performance gap between convolutions and attention-based models. ConvNeXt’s clean, hierarchical structure makes it efficient for both pretraining and fine-tuning across a wide range of visual recognition tasks. It achieves competitive or superior results on ImageNet and downstream datasets while being easier to deploy and train than transformers. The repository provides pretrained models, training recipes, and ablation studies demonstrating how incremental design choices collectively yield state-of-the-art performance.
Features
- Modernized CNN architecture inspired by Vision Transformer design principles
- Large kernel convolutions and inverted bottleneck blocks for enhanced representation
- Layer normalization and GELU activation for improved stability and accuracy
- Hierarchical structure with strong scaling properties across model sizes
- Pretrained checkpoints and training recipes for ImageNet and downstream tasks
- Efficient deployment and compatibility with existing CNN-based systems
Programming Language
Python
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/convnext.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
