内容提示: Are we done with ImageNet?Lucas Beyer 1∗ Olivier J. Hénaff 2∗ Alexander Kolesnikov 1∗ Xiaohua Zhai 1∗ Aäron van den Oord 2∗1 Google Brain (Zürich, CH) and 2 DeepMind (London, UK)AbstractYes, and no. We ask whether recent progress on the ImageNet classif ...
Are we done with ImageNet? 来自 arXiv.org 喜欢 0 阅读量: 299 作者:L Beyer,OJ Hénaff,A Kolesnikov,X Zhai,AVD Oord 摘要: Yes, and no. We ask whether recent progress on the ImageNet classification benchmark continues to represent meaningful generalization, or whether the community has ...
Based on the compressed sampling theorem to compress and expand small sample data, we use CNN to directly classify the compressed sampling data features. Compared with the original image input, compressing the input can greatly reduce the network's demand for samples. In addition, the surface ...
Based on the compressed sampling theorem to compress and expand small sample data, we use CNN to directly classify the compressed sampling data features. Compared with the original image input, compressing the input can greatly reduce the network's demand for samples. In addition, the surface ...
As a point of comparison, we include avg. diversity measures between two linear classifiers fine-tuned with random splits on half of ImageNet,3 denoted in orange in Figure 5. Models are more confident where they excel. In order for the ensemble model to be effective, it should leverag...
However, as with everything related to AI, it’s always an arms race between fraudsters and modern deepfake detectors. Coming out of International Fraud Awareness Week, we wanted to provide a reality check into the capabilities and advancements of deepfake detectors over the last few years - a...
Many people relate “artificial intelligence” with “big data.” There’s a reason for that: some of the most prominent AI breakthroughs in the past decade have relied on enormous data sets. Image ___ made great progress in the 2010s thanks to the development of ImageNet, a data set co...
On that "country level" we should also consider for the model hyperparameter tuning and such. Sure, but that is a fixed cost which is now in the past, and need never be done again. The MuZero code is written, and the hyperparameters are done. They are amortized over every ...
We first downloaded a version of AlexNet (pre-trained with the imagenet classification dataset). We then cropped the network at the ‘fc7’ layer, and added a customized classification layer (containing 10 output nodes; corresponding to our objects) at the backend. We then trained this network...
AiAi.care project is teaching computers to "see" chest X-rays and interpret them how a human Radiologist would. We are using 700,000 Chest X-Rays + Deep Learning to build an FDA 💊 approved, open-source screening tool for Tuberculosis and Lung Cancer.