Machine Learning, as understood in this context of Image Analysis with DeepLearning, is a pretty young field. I'd place 2012 and Hinton's work then as the start

Machine Learning, as understood in this context of Image Analysis with DeepLearning, is a pretty young field. I'd place 2012 and Hinton's work then as the starting point and maybe even 2015 when ResNet was introduced. That is in the best case 9 years. (AI and ML exist since Turing in 50s but in many forms) Fortran was made public in 1956 and only 12 years later use of goto considered harmful was published. It is still a young field with everyone wanting to get in, many without any clear goals or standards, just to publish anything. Trash certainly and from what I've seen myself by reading papers a lot of very badly hidden plagiarism. A ML analog to use of goto considered harmful is very much needed to raise the bar. Scientific integrity, consideration for the greater whole, 100% replicability and basis on sound principles of mathematical theory, most notably probability and statistics. Yet that is the price of freedom from corporations and big universities. Science for everyone and by everyone. We can't let bad apples, even if they are the vast majority, force us into willing deposition of our rights. If sites like ArXiV went away then access to knowledge would cease under the boots of Springer and Elsevier. Some sort of blind rating papers incognito could perhaps help to have the good rise above the rest. No information on authors, no information on raters. Just votes mirroring the quality, or lack of, w.r.t the paper.