code-paper-recurrent

Introduction

This is a folder to save some code to recurrent some algorithm in some papers.
Then I will introduce these algorithm:

[MLHM] = multiscale local homogeneity measure

[REF] Nie J, Qu S, Wei Y, et al. An infrared small target detection method based on multiscale local homogeneity measure[J]. Infrared Physics & Technology, 2018, 90: 186-194.

[ALCM-LSK] = adaptive local contrast measure - local steering kernel

[REF] Li Y, Zhang Y. Robust infrared small target detection using local steering kernel reconstruction[J]. Pattern Recognition, 2018, 77: 113-125.

[Kernel Regression] for image processing

[REF] Takeda H, Farsiu S, Milanfar P. Kernel regression for image processing and reconstruction[J]. 2006
[ToolBox] Kernel Regression-Based Image Processing ToolBox for MATLAB
(Tips) If I can find the toolbox corresponding the paper, I will put the link on this page without rewrite the code.

[Unsupervised ridge detection] = second order anisotropic Gaussian kernels(AGK)

[REF] Lopez-Molina C, De Ulzurrun G V D, Baetens J M, et al. Unsupervised ridge detection using second order anisotropic Gaussian kernels[J]. Signal Processing, 2015, 116: 55-67.

[Dual-Threshold Computation] = Bowstring-Based Method for Adaptive Canny Edge Detector

[REF] Liu X, Yu Y, Liu B, et al. Bowstring-based dual-threshold computation method for adaptive Canny edge detector[C]//2013 28th International Conference on Image and Vision Computing New Zealand (IVCNZ 2013). IEEE, 2013: 13-18. ❗❗ATTENTION❗❗ there is a defect in the implement, due to the inexplicit instruction about the procedure of the algorithm. So if you have some useful idea, welcome to contact me and discuss.

[Bayesian inference for adaptive low rank] = sparse and low-rank model solver by bayesian method and ADMM

[REF] Jia X, Feng X, Wang W, et al. Bayesian inference for adaptive low rank and sparse matrix estimation[J]. Neurocomputing, 2018, 291: 71-83.

[Kernel regression for non-invasive glucose detection] = Accuracy Enhancement for Noninvasive Glucose Estimation

[REF] Pai P P, De A, Banerjee S. Accuracy Enhancement for Noninvasive Glucose Estimation Using Dual-Wavelength Photoacoustic Measurements and Kernel-Based Calibration[J]. Ieee Transactions on Instrumentation and Measurement, 2018, 67(1): 126-36 (Tips) Using which kernel means the shape of the fitting function, for example: polynomial kernel == polynomial function(personal understanding)

My paper - special issue

[TK-main energy and blood glucose detection] = Blood glucose detection based on Teager-Kaiser main energy of photoacoustic signal (Here is the author!!)

[REF] Long H, Chen B, Li W, Xian Y, Peng Z. Blood glucose detection based on Teager-Kaiser main energy of photoacoustic signal. Comput Biol Med. 2021 Jul;134:104552. doi: 10.1016/j.compbiomed.2021.104552. Epub 2021 Jun 8. PMID: 34144363. [ToolBox] ValoMC toolbox + k-Wave toolbox(For simulation)
[ToolBox] Time-Frequency Toolbox-For Use with Matlab (Tips) The real data is saved in real-data.mat / The simulated data should be generated by yourself(codes are provided).

[Evidence Theory] = A New Structure of the Focal Element in Object (Here is the author!!)

[REF] Long H, Peng Z, Deng Y. A new structure of the focal element in object recognition[J]. International Journal of Intelligent Systems, 2021.
[Usage] Experiments 4.1(using pignistic probability transform to classify): demo_newStructure.m(using new structure)/demo_tradition.m(using traditional structure)
[Usage] Experiments 4.2(using the proposed method): demo.m/ demo_classical.m(traditional methods for comparison--svm, REPtree, knn)
[Usage] demo_iris.m is just a demo for debug(can see the internal debugging information through this script)
[Tips] LoadXXX_new(or tradition).m is the corresponding script used to load the dataset('new' means the new structure/ 'tradition' means the traditional structure)

[WaveFeature and evidential regression for blood glucose detection] = Evidential regression-based blood glucose detection using waveform features(Here is the author!!)

[REF] Hongfeng, Long; Yang, Chunping; Li, Wei; Peng, Zhenming; Pu, Tian (2021): Evidential regression-based blood glucose detection using waveform features. TechRxiv. Preprint. https://doi.org/10.36227/techrxiv.17128457.v1 (preprint)
[Usage] Experiments C(using the proposed method): demo.m
[ToolBox] Evidential classification and regression (MATLAB)
[Tips] The real data is saved in real-data.mat(The human finger’s photoacoustic signal)
[Tips] The real data for Experiments B is saved in real-data2.mat(46 samples)

Purpose

This is a storehouse to store some runnable codes about some algorithms.
I will upgrade the storehouse when I have some free time or have some new codes, but not periodically. So please don't push the author !!!

Author

[ORCID] 0000-0002-8201-5948 [Tips] the algorithm codes in this folder are written by myself, but I will use some function from some toolbox. Thanks for predecessor!!

Language

MATLAB (currently)
C++ (future)

History

2018-10-17 upgraded LSK and MLHM algorithm.
2018-10-24 added a link of toolobox, "Kernel Regression-Based Image Processing ToolBox for MATLAB".
2019-3-1 update "Unsupervised ridge detection" and "Dual-Threshold Computation" algorithm.
2019-3-13 update "Bayesian inference for adaptive low rank" algorithm.
2021-9-1 update "TK-main energy and blood glucose detection" project(including simulation and real test).
2021-9-1 update "Kernel regression for non-invasive glucose detection" algorithm.
2021-10-18 update "A New Structure of the Focal Element in Object" algorithm and code.
2021-12-14 update "Evidential regression-based blood glucose detection using waveform features" algorithm and code.
2022-4-26 update "Evidential regression-based blood glucose detection using waveform features", fix some bugs and reconstruct some functions.
2022-5-10 update fix the bug in the "Evidential regression-based blood glucose detection using waveform features".

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