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• We fine-tune 7 models including ViTs, DINO, CLIP, ConvNeXt, ResNet, on

We fine-tune 7 models including ViTs, DINO, CLIP, ConvNeXt, ResNet, on

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PDF) Vision Models Can Be Efficiently Specialized via Few-Shot Task-Aware Compression

PDF) Adversarial Attacks on Foundational Vision Models

We fine-tune 7 models including ViTs, DINO, CLIP, ConvNeXt, ResNet, on

A Broad Study of Pre-training for Domain Generalization and Adaptation

Sébastien BUBECK, Princeton University, New Jersey, PU, Department of Operations Research and Financial Engineering

Remote Sensing, Free Full-Text

PDF] ConvNeXt V2: Co-designing and Scaling ConvNets with Masked

2304.12210] A Cookbook of Self-Supervised Learning

Review — ConvNeXt: A ConvNet for the 2020s, by Sik-Ho Tsang

timm (0.9.12) - pypi Package Quality

The freeze out distribution, f f ree (x, p), in the Rest Frame of the

Recent Developments and Views on Computer Vision x Transformer

A Broad Study of Pre-training for Domain Generalization and Adaptation

PDF) Adversarial Attacks on Foundational Vision Models