Resource of free step by step video how to guides to get you started with machine learning.
Tuesday, May 26, 2020
A critical analysis of self-supervision, or what we can learn from a single image (Paper Explained)
Does self-supervision really need a lot of data? How low can you go? This paper shows that a single image is enough to learn the lower layers of a deep neural network. Interestingly, more data does not appear to help as long as enough data augmentation is applied. OUTLINE: 0:00 - Overview 1:40 - What is self-supervision 4:20 - What does this paper do 7:00 - Linear probes 11:15 - Linear probe results 17:10 - Results 22:25 - Learned Features https://ift.tt/2TCJtow Abstract: We look critically at popular self-supervision techniques for learning deep convolutional neural networks without manual labels. We show that three different and representative methods, BiGAN, RotNet and DeepCluster, can learn the first few layers of a convolutional network from a single image as well as using millions of images and manual labels, provided that strong data augmentation is used. However, for deeper layers the gap with manual supervision cannot be closed even if millions of unlabelled images are used for training. We conclude that: (1) the weights of the early layers of deep networks contain limited information about the statistics of natural images, that (2) such low-level statistics can be learned through self-supervision just as well as through strong supervision, and that (3) the low-level statistics can be captured via synthetic transformations instead of using a large image dataset. Authors: Yuki M. Asano, Christian Rupprecht, Andrea Vedaldi Thumbnail Image: https://ift.tt/2zng2zV Links: YouTube: https://www.youtube.com/c/yannickilcher Twitter: https://twitter.com/ykilcher BitChute: https://ift.tt/38iX6OV Minds: https://ift.tt/37igBpB
Subscribe to:
Post Comments (Atom)
-
JavaやC++で作成された具体的なルールに従って動く従来のプログラムと違い、機械学習はデータからルール自体を推測するシステムです。機械学習は具体的にどのようなコードで構成されているでしょうか? 機械学習ゼロからヒーローへの第一部ではそのような疑問に応えるため、ガイドのチャー...
-
#deeplearning #noether #symmetries This video includes an interview with first author Ferran Alet! Encoding inductive biases has been a lo...
-
Using GPUs in TensorFlow, TensorBoard in notebooks, finding new datasets, & more! (#AskTensorFlow) [Collection] In a special live ep...
-
How to Do PS2 Filter (Tiktok PS2 Filter Tutorial), AI tiktok filter Create your own PS2 Filter photos with this simple guide! 🎮📸 Please...
-
Challenge scenario You were recently hired as a Machine Learning Engineer at a startup movie review website. Your manager has tasked you wit...
-
#ai #attention #transformer #deeplearning Transformers are famous for two things: Their superior performance and their insane requirements...
-
Visual scenes are often comprised of sets of independent objects. Yet, current vision models make no assumptions about the nature of the p...
-
Why are humans so good at video games? Maybe it's because a lot of games are designed with humans in mind. What happens if we change t...
-
#alibi #transformers #attention Transformers are essentially set models that need additional inputs to make sense of sequence data. The mo...
-
Future skill Machine Learning Free Course -https://futureskillsprime.in/course/machine-learning-linear-regressionfree ai and machine learnin...
No comments:
Post a Comment