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DOIs for this ISSN

Showing the top 5 of 96 DOIs, ordered by correction priority.

#	Title	Missing	Priority	Citations
1	Semi-supervised learning of hyperspectral image segmentation… (10.1255/jsi.2018.a7)	Abstract References License	52.42	4
2	A survey of band selection techniques for hyperspectral imag… (10.1255/jsi.2020.a5)	References	40.58	41
3	An identification method for defective tablets by distributi… (10.1255/jsi.2019.a15)	References ORCID	38.91	5
4	Spectral similarity algorithm-based image classification for… (10.1255/jsi.2020.a14)	References ORCID	38.91	5
5	Classification of different tomato seed cultivars by multisp… (10.1255/jsi.2016.a1)	References	38.29	33
6	Comprehensive review on land use/land cover change classific… (10.1255/jsi.2020.a8)	References	36.93	29
7	Development of a classification algorithm for efficient hand… (10.1255/jsi.2018.a13)	References	35.37	25
8	Application of hyperspectral imaging and chemometrics for cl… (10.1255/jsi.2019.a1)	References	34.51	23
9	Hyperspectral imaging for textile sorting in the visible–nea… (10.1255/jsi.2019.a17)	References	34.51	23
10	Can hyperspectral imaging be used to map corrosion products… (10.1255/jsi.2018.a10)	References	32.53	19
11	Raman imaging of protein in a model cheese system (10.1255/jsi.2020.a9)	References ORCID	30.10	3
12	Hyperspectral image non-linear unmixing using joint extrinsi… (10.1255/jsi.2022.a4)	References ORCID	30.10	3
13	Inverting the PROSAIL canopy reflectance model using neural… (10.1255/jsi.2010.a2)	References	28.65	13
14	Application of calibrations to hyperspectral images of food… (10.1255/jsi.2017.a4)	References	28.65	13
15	The hype in spectral imaging (10.1255/jsi.2020.a4)	References	28.65	13
16	Short communication: Laboratory imaging spectroscopy of soil… (10.1255/jsi.2011.a2)	References	26.98	11
17	Hyperspectral photoluminescence imaging of defects in solar… (10.1255/jsi.2016.a8)	References	26.03	10
18	Hyperspectral imaging as a tool for assessing coral health u… (10.1255/jsi.2019.a7)	References	26.03	10
19	Performance comparison of aperture-less and confocal infrare… (10.1255/jsi.2019.a8)	References	26.03	10
20	Vitamin C distribution in acerola fruit by near infrared hyp… (10.1255/jsi.2016.a6)	References	25.00	9
21	Assessment of pesticide coating on cereal seeds by near infr… (10.1255/jsi.2017.a1)	References	25.00	9
22	Multivariate data modelling for de-shadowing of airborne hyp… (10.1255/jsi.2017.a2)	References ORCID	23.86	2
23	Hyperspectral imaging of the degradation of meat and compari… (10.1255/jsi.2019.a9)	References ORCID	23.86	2
24	Applying spectral analysis for identification of alteration… (10.1255/jsi.2020.a15)	References ORCID	23.86	2
25	Deep learning classifiers for near infrared spectral imaging… (10.1255/jsi.2020.a19)	References	23.86	8
26	Raman and Fourier transform infrared hyperspectral imaging t… (10.1255/jsi.2019.a3)	References	22.58	7
27	Comparison of spectral selection methods in the development… (10.1255/jsi.2019.a4)	References	22.58	7
28	Terahertz spectroscopy and imaging for gastric cancer diagno… (10.1255/jsi.2020.a2)	References	22.58	7
29	A modified Cuckoo Search algorithm based optimal band subset… (10.1255/jsi.2020.a6)	References	22.58	7
30	Exploring field-of-view non-uniformities produced by a hand-… (10.1255/jsi.2011.a1)	References	21.13	6
31	Monitoring the change in colour of meat: A comparison of tra… (10.1255/jsi.2012.a1)	References	21.13	6
32	High-resolution mapping of upland swamp vegetation using an… (10.1255/jsi.2017.a6)	References	21.13	6
33	Concentration monitoring with near infrared chemical imaging… (10.1255/jsi.2018.a5)	References	21.13	6
34	Ultraviolet-visible/near infrared spectroscopy and hyperspec… (10.1255/jsi.2020.a18)	References	21.13	6
35	New insights in osteocyte imaging by synchrotron radiation (10.1255/jsi.2020.a3)	References	21.13	6
36	An outlook: machine learning in hyperspectral image classifi… (10.1255/jsi.2022.a1)	References	21.13	6
37	A semi-supervised cycle-GAN neural network for hyperspectral… (10.1255/jsi.2022.a2)	References	21.13	6
38	Reflectance spectra and AVIRIS-NG airborne hyperspectral dat… (10.1255/jsi.2022.a9)	References	21.13	6
39	Use of spectral pre-processing methods to compensate for the… (10.1255/jsi.2010.a1)	References	19.45	5
40	Rapid identification of Salmonella serotypes through hypersp… (10.1255/jsi.2016.a4)	References	19.45	5
41	Classification in hyperspectral images by independent compon… (10.1255/jsi.2018.a4)	References	19.45	5
42	Quantification of leghaemoglobin content in pea nodules base… (10.1255/jsi.2018.a9)	References	19.45	5
43	Characterisation of oxide layers on technical copper based o… (10.1255/jsi.2019.a10)	References	19.45	5
44	Comparison of 2D and 3D semantic segmentation in urban areas… (10.1255/jsi.2022.a11)	References	19.45	5
45	Use of infrared hyperspectral imaging as an aid for paint id… (10.1255/jsi.2016.a2)	References	17.47	4
46	Weighted fuzzy clustering for (fuzzy) constraints in multiva… (10.1255/jsi.2016.a7)	References	17.47	4
47	Estimation of phosphorus-based flame retardant in wood by hy… (10.1255/jsi.2018.a3)	References	17.47	4
48	Unsupervised classification of individual foodborne bacteria… (10.1255/jsi.2018.a6)	References	17.47	4
49	Adaptive hierarchical clustering for hyperspectral image cla… (10.1255/jsi.2019.a11)	References	17.47	4
50	Matrix-assisted ionisation in vacuum mass spectrometry and i… (10.1255/jsi.2019.a12)	References	17.47	4