Reference

[1]

Deonie Allen, Steve Allen, Sajjad Abbasi, Alex Baker, Melanie Bergmann, Janice Brahney, Tim Butler, Robert A. Duce, Sabine Eckhardt, Nikolaos Evangeliou, Tim Jickells, Maria Kanakidou, Peter Kershaw, Paolo Laj, Joseph Levermore, Daoji Li, Peter Liss, Kai Liu, Natalie Mahowald, Pere Masque, Dusan Materic, Andrew G. Mayes, Paul McGinnity, Iolanda Osvath, Kimberly A. Prather, Joseph M. Prospero, Laura E. Revell, Sylvia G. Sander, Won Joon Shim, Jonathan Slade, Ariel Stein, Oksana Tarasova, and Stephanie Wright. Microplastics and nanoplastics in the marine-atmosphere environment. Nature Reviews Earth & Environment, 3(6):393–405, Jun 2022. URL: https://doi.org/10.1038/s43017-022-00292-x, doi:10.1038/s43017-022-00292-x.

[2]

Leon Bottou. Stochastic Gradient Descent Tricks, pages 421–436. Springer Berlin Heidelberg, Berlin, Heidelberg, 2012. URL: https://doi.org/10.1007/978-3-642-35289-8_25, doi:10.1007/978-3-642-35289-8_25.

[3]

Wai-Ki Ching, Delin Chu, Li-Zhi Liao, and Xiaoyan Wang. Regularized orthogonal linear discriminant analysis. Pattern Recognition, 45(7):2719–2732, 2012. URL: https://www.sciencedirect.com/science/article/pii/S0031320312000283, doi:https://doi.org/10.1016/j.patcog.2012.01.007.

[4]

Ross Girshick. Fast r-cnn. 2015. URL: https://arxiv.org/abs/1504.08083, doi:10.48550/ARXIV.1504.08083.

[5]

Ross Girshick, Jeff Donahue, Trevor Darrell, and Jitendra Malik. Rich feature hierarchies for accurate object detection and semantic segmentation. 2013. URL: https://arxiv.org/abs/1311.2524, doi:10.48550/ARXIV.1311.2524.

[6]

Ian J. Goodfellow, Yoshua Bengio, and Aaron Courville. Deep Learning. MIT Press, Cambridge, MA, USA, 2016. URL: http://www.deeplearningbook.org.

[7]

Charbel Harb, Nishan Pokhrel, and Hosein Foroutan. Quantification of the emission of atmospheric microplastics and nanoplastics via sea spray. Environmental Science & Technology Letters, 10(6):513–519, 2023. URL: https://doi.org/10.1021/acs.estlett.3c00164, arXiv:https://doi.org/10.1021/acs.estlett.3c00164, doi:10.1021/acs.estlett.3c00164.

[8]

Trevor Hastie, Robert Tibshirani, and J. H. Friedman. The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer, New York, NY, USA, 2009.

[9]

Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani. An Introduction to Statistical Learning: with Applications in R. Springer, New York, NY, USA, 2013. URL: https://www.statlearning.com.

[10]

Frederic DL. Leusch, Hsuan-Cheng Lu, Kushani Perera, Peta A. Neale, and Shima Ziajahromi. Analysis of the literature shows a remarkably consistent relationship between size and abundance of microplastics across different environmental matrices. Environmental Pollution, 319:120984, 2023. URL: https://www.sciencedirect.com/science/article/pii/S0269749122021996, doi:https://doi.org/10.1016/j.envpol.2022.120984.

[11]

Beijing Academy of Artificial Intelligence. Suggested notation for machine learning. 2020. URL: https://github.com/mazhengcn/suggested-notation-for-machine-learning.

[12]

K. B. Petersen and M. S. Pedersen. The matrix cookbook. nov 2012. Version 20121115. URL: http://www2.compute.dtu.dk/pubdb/pubs/3274-full.html.

[13]

H. Pishro-Nik. Introduction to Probability, Statistics, and Random Processes. Kappa Research LLC, 2014. URL: https://www.probabilitycourse.com.

[14]

Joseph Redmon and Ali Farhadi. YOLO9000: better, faster, stronger. CoRR, 2016. URL: http://arxiv.org/abs/1612.08242, arXiv:1612.08242.

[15]

Joseph Redmon and Ali Farhadi. Yolov3: an incremental improvement. 2018. URL: https://arxiv.org/abs/1804.02767, doi:10.48550/ARXIV.1804.02767.

[16]

Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun. Faster r-cnn: towards real-time object detection with region proposal networks. 2015. URL: https://arxiv.org/abs/1506.01497, doi:10.48550/ARXIV.1506.01497.

[17]

Andrew Rothman. Ols regression, gauss-markov, blue, and understanding the math. Jun 2020. [Online; accessed 21-February-2023]. URL: https://towardsdatascience.com/ ols-linear-regression-gauss-markov-blue-and-understanding-the- math-453d7cc630a5.

[18]

Wikipedia. Definite Matrix. 2023. [Online; accessed 9-May-2023]. URL: https://en.wikipedia.org/wiki/Definite_matrix.

[19]

Wikipedia. Gauss–Markov Theorem. 2023. [Online; accessed 21-February-2023]. URL: https://en.wikipedia.org/wiki/Gauss–Markov_theorem.

[20]

Wikipedia. Gram Matrix. 2023. [Online; accessed 9-May-2023]. URL: https://en.wikipedia.org/wiki/Gram_matrix.

[21]

Wikipedia. Moore–Penrose Inverse. 2023. [Online; accessed 9-May-2023]. URL: https://en.wikipedia.org/wiki/Moore-Penrose_inverse.

[22]

Wikipedia. Pooled Variance. 2023. [Online; accessed 7-May-2023]. URL: https://en.wikipedia.org/wiki/Pooled_variance.

[23]

Wikipedia. Ridge Regression. 2023. [Online; accessed 9-May-2023]. URL: https://en.wikipedia.org/wiki/Ridge_regression.

[24]

Wikipedia. Simple Linear Regression. 2023. [Online; accessed 17-March-2023]. URL: https://en.wikipedia.org/wiki/Simple_linear_regression.

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