Every fixed finite feedforward neural network definable in an o-minimal structure has finite sample complexity in the agnostic PAC setting.
Deep residual learning for image recognition
4 Pith papers cite this work. Polarity classification is still indexing.
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DINO reaches 51.3 AP on COCO val2017 with a ResNet-50 backbone after 24 epochs, a +2.7 AP gain over the prior best DETR variant.
Optimal softmax temperature is analytically determined by feature dimensionality, adjusted by fitted coefficients and batch norm for model- and domain-robust classification.
Ensemble of four CNNs classifies elliptical and spiral galaxies in S-PLUS images with approximately 99% accuracy on a held-out test set.
citing papers explorer
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Every Feedforward Neural Network Definable in an o-Minimal Structure Has Finite Sample Complexity
Every fixed finite feedforward neural network definable in an o-minimal structure has finite sample complexity in the agnostic PAC setting.
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DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection
DINO reaches 51.3 AP on COCO val2017 with a ResNet-50 backbone after 24 epochs, a +2.7 AP gain over the prior best DETR variant.
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Analytical Softmax Temperature Setting from Feature Dimensions for Model- and Domain-Robust Classification
Optimal softmax temperature is analytically determined by feature dimensionality, adjusted by fitted coefficients and batch norm for model- and domain-robust classification.
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Morphological Classification of Galaxies in S-PLUS using an Ensemble of Convolutional Networks
Ensemble of four CNNs classifies elliptical and spiral galaxies in S-PLUS images with approximately 99% accuracy on a held-out test set.