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Neural architecture search (NAS) has witnessed prevailing success in image classification and (very recently) segmentation tasks.
#3 best model for Image Generation on CIFAR-10
The learning rate warmup heuristic achieves remarkable success in stabilizing training, accelerating convergence and improving generalization for adaptive stochastic optimization algorithms like RMSprop and Adam.
Semi-supervised learning, i. e. jointly learning from labeled an unlabeled samples, is an active research topic due to its key role on relaxing human annotation constraints.
In addition to this dataset, we disseminate an additional real world handwritten dataset (with $10k$ images), which we term as the Dig-MNIST dataset that can serve as an out-of-domain test dataset.
Long-range dependencies modeling, widely used in capturing spatiotemporal correlation, has shown to be effective in CNN dominated computer vision tasks.
#13 best model for Object Detection on PASCAL VOC 2007
In this paper, we systematically study the impact of different kernel sizes, and observe that combining the benefits of multiple kernel sizes can lead to better accuracy and efficiency.
#34 best model for Image Classification on ImageNet
The vast majority of successful deep neural networks are trained using variants of stochastic gradient descent (SGD) algorithms.