Hello everyone,
I’m requesting an arXiv endorsement for a submission to the cs.CV category.
https://arxiv.org/auth/endorse?x=4MU8YU
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http://arxiv.org/auth/endorse.php
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Endorsement Code: 4MU8YU
My work is in deep learning / computer vision, with a focus on:
CNNs and Vision Transformers,
normalization methods,
activation functions,
and training recipes for image classification.
I am preparing a paper on normalization-free architectures and a new activation function. Some of the main results include:
ResNet18:
CIFAR-10: 97.12 ± 0.14 top-1, 99.86 ± 0.05 top-5
CIFAR-100: 83.13 ± 0.19 top-1, 96.20 ± 0.40 top-5
ResNet50 on ImageNet-1K:
78.85 ± 0.25 top-1 over 3 runs (90 epochs)
VIT adapted to CIFAR:
improved performance over the LN+GELU baseline on both CIFAR-10 and CIFAR-100
Additional CIFAR-10 result:
ResNet18: 93.44% top-1 accuracy with batch size = 1
The main idea of the paper is to replace explicit normalization with a new stabilization mechanism and gated activations, and to demonstrate that this approach works across CNNs, Vision Transformers, and ImageNet-scale training.
If anyone is willing to provide an endorsement for cs.CV, I would be very grateful. I’d be happy to share more details about the manuscript or my research background if needed.
Thank you very much for your time and consideration.