{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,10]],"date-time":"2026-03-10T12:02:58Z","timestamp":1773144178080,"version":"3.50.1"},"publisher-location":"Cham","reference-count":32,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031314162","type":"print"},{"value":"9783031314179","type":"electronic"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.1007\/978-3-031-31417-9_14","type":"book-chapter","created":{"date-parts":[[2023,5,6]],"date-time":"2023-05-06T12:02:31Z","timestamp":1683374551000},"page":"176-189","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Non-invasive Haemoglobin Estimation Using Different Colour and\u00a0Texture Features of\u00a0Palm"],"prefix":"10.1007","author":[{"given":"Abhishek","family":"Kesarwani","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sunanda","family":"Das","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mamata","family":"Dalui","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dakshina Ranjan","family":"Kisku","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,5,7]]},"reference":[{"key":"14_CR1","unstructured":"Agarap, A.F.: Deep learning using rectified linear units. arXiv preprint arXiv:1803.08375 (2018)"},{"key":"14_CR2","doi-asserted-by":"crossref","unstructured":"Ahsan, et al.: A novel real-time non-invasive hemoglobin level detection using video images from smartphone camera. In: 2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC), vol. 1, pp. 967\u2013972. IEEE (2017)","DOI":"10.1109\/COMPSAC.2017.29"},{"key":"14_CR3","doi-asserted-by":"crossref","unstructured":"Beraha, M., Metelli, A.M., Papini, M., Tirinzoni, A., Restelli, M.: Feature selection via mutual information: new theoretical insights. In: 2019 International Joint Conference on Neural Networks (IJCNN), pp. 1\u20139. IEEE (2019)","DOI":"10.1109\/IJCNN.2019.8852410"},{"issue":"1","key":"14_CR4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/1749-8090-8-159","volume":"8","author":"CS Bruells","year":"2013","unstructured":"Bruells, C.S., et al.: Accuracy of the Masimo pronto-7\u00ae system in patients with left ventricular assist device. J. Cardiothorac. Surg. 8(1), 1\u20136 (2013)","journal-title":"J. Cardiothorac. Surg."},{"key":"14_CR5","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"269","DOI":"10.1007\/978-3-540-30125-7_34","volume-title":"Image Analysis and Recognition","author":"Y Chen","year":"2004","unstructured":"Chen, Y., Hao, P., Dang, A.: Optimal transform in perceptually uniform color space and its application in image coding. In: Campilho, A., Kamel, M. (eds.) ICIAR 2004. LNCS, vol. 3211, pp. 269\u2013276. Springer, Heidelberg (2004). https:\/\/doi.org\/10.1007\/978-3-540-30125-7_34"},{"key":"14_CR6","doi-asserted-by":"publisher","unstructured":"Das, S., Kesarwani, A., Kisku, D.R., Dalui, M.: Non-invasive haemoglobin prediction using nail color features: an approach of dimensionality reduction. In: Huang, DS., Jo, KH., Jing, J., Premaratne, P., Bevilacqua, V., Hussain, A. (eds.) ICIC 2022. LNCS, vol. 13393, pp. 811\u2013824. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-13870-6_66","DOI":"10.1007\/978-3-031-13870-6_66"},{"key":"14_CR7","unstructured":"Florestiyanto, M.Y., Peksi, N.J.: Non-invasive anemia screening using nails and palms photos. In: Proceeding of LPPM UPN \u201cVeteran\u201d Yogyakarta Conference Series 2020-Engineering and Science Series, vol. 1, pp. 311\u2013318 (2020)"},{"key":"14_CR8","unstructured":"Ford, A., Roberts, A.: Colour Space Conversions, pp. 1\u201331. Westminster University, London (1998)"},{"key":"14_CR9","doi-asserted-by":"crossref","unstructured":"Fuadah, Y.N., Sa\u2019idah, S., Wijayanto, I., Patmasari, R., Magdalena, R.: Non invasive anemia detection in pregnant women based on digital image processing and k-nearest neighbor. In: 2020 3rd International Conference on Biomedical Engineering (IBIOMED), pp. 60\u201364. IEEE (2020)","DOI":"10.1109\/IBIOMED50285.2020.9487605"},{"issue":"7","key":"14_CR10","doi-asserted-by":"publisher","first-page":"577","DOI":"10.1016\/j.ndteint.2004.03.004","volume":"37","author":"E Gadelmawla","year":"2004","unstructured":"Gadelmawla, E.: A vision system for surface roughness characterization using the gray level co-occurrence matrix. NDT & e Int. 37(7), 577\u2013588 (2004)","journal-title":"NDT & e Int."},{"issue":"6","key":"14_CR11","doi-asserted-by":"publisher","first-page":"8520","DOI":"10.1109\/JSEN.2020.3044386","volume":"21","author":"S Ghosal","year":"2020","unstructured":"Ghosal, S., Das, D., Udutalapally, V., Talukder, A.K., Misra, S.: shemo: Smartphone spectroscopy for blood hemoglobin level monitoring in smart anemia-care. IEEE Sens. J. 21(6), 8520\u20138529 (2020)","journal-title":"IEEE Sens. J."},{"issue":"6","key":"14_CR12","doi-asserted-by":"publisher","first-page":"1657","DOI":"10.1109\/TIP.2010.2044957","volume":"19","author":"Z Guo","year":"2010","unstructured":"Guo, Z., Zhang, L., Zhang, D.: A completed modeling of local binary pattern operator for texture classification. IEEE Trans. Image Process. 19(6), 1657\u20131663 (2010)","journal-title":"IEEE Trans. Image Process."},{"key":"14_CR13","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"195","DOI":"10.1007\/3-540-59497-3_175","volume-title":"From Natural to Artificial Neural Computation","author":"J Han","year":"1995","unstructured":"Han, J., Moraga, C.: The influence of the sigmoid function parameters on the speed of backpropagation learning. In: Mira, J., Sandoval, F. (eds.) IWANN 1995. LNCS, vol. 930, pp. 195\u2013201. Springer, Heidelberg (1995). https:\/\/doi.org\/10.1007\/3-540-59497-3_175"},{"key":"14_CR14","doi-asserted-by":"publisher","DOI":"10.1016\/j.visres.2021.107976","volume":"192","author":"L Jiang","year":"2022","unstructured":"Jiang, L., et al.: Skin color measurements before and after two weeks of sun exposure. Vision. Res. 192, 107976 (2022)","journal-title":"Vision. Res."},{"issue":"2","key":"14_CR15","doi-asserted-by":"publisher","first-page":"247","DOI":"10.1016\/j.hoc.2015.11.002","volume":"30","author":"NJ Kassebaum","year":"2016","unstructured":"Kassebaum, N.J., Collaborators, G.A., et al.: The global burden of anemia. Hematol. Oncol. Clin. North Am. 30(2), 247\u2013308 (2016)","journal-title":"Hematol. Oncol. Clin. North Am."},{"key":"14_CR16","unstructured":"Kingma, D.P., Ba, J.: Adam: a method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014)"},{"issue":"7553","key":"14_CR17","doi-asserted-by":"publisher","first-page":"436","DOI":"10.1038\/nature14539","volume":"521","author":"Y LeCun","year":"2015","unstructured":"LeCun, Y., Bengio, Y., Hinton, G.: Deep learning. Nature 521(7553), 436\u2013444 (2015)","journal-title":"Nature"},{"issue":"6","key":"14_CR18","doi-asserted-by":"publisher","first-page":"1424","DOI":"10.1213\/ANE.0b013e3181fc74b9","volume":"111","author":"MR Macknet","year":"2010","unstructured":"Macknet, M.R., Allard, M., Applegate, R.L., Rook, J., et al.: The accuracy of noninvasive and continuous total hemoglobin measurement by pulse co-oximetry in human subjects undergoing hemodilution. Anesthesia Analgesia 111(6), 1424\u20131426 (2010)","journal-title":"Anesthesia Analgesia"},{"issue":"1","key":"14_CR19","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41467-018-07262-2","volume":"9","author":"RG Mannino","year":"2018","unstructured":"Mannino, R.G., et al.: Smartphone app for non-invasive detection of anemia using only patient-sourced photos. Nat. Commun. 9(1), 1\u201310 (2018)","journal-title":"Nat. Commun."},{"issue":"5","key":"14_CR20","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/0041-5553(64)90137-5","volume":"4","author":"BT Polyak","year":"1964","unstructured":"Polyak, B.T.: Some methods of speeding up the convergence of iteration methods. USSR Comput. Math. Math. Phys. 4(5), 1\u201317 (1964)","journal-title":"USSR Comput. Math. Math. Phys."},{"key":"14_CR21","doi-asserted-by":"crossref","unstructured":"Rahimzadeganasl, A., Sertel, E.: Automatic building detection based on CIE luv color space using very high resolution pleiades images. In: 2017 25th Signal Processing and Communications Applications Conference (SIU), pp. 1\u20134. IEEE (2017)","DOI":"10.1109\/SIU.2017.7960711"},{"issue":"5","key":"14_CR22","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1109\/38.946629","volume":"21","author":"E Reinhard","year":"2001","unstructured":"Reinhard, E., Adhikhmin, M., Gooch, B., Shirley, P.: Color transfer between images. IEEE Comput. Graph. Appl. 21(5), 34\u201341 (2001)","journal-title":"IEEE Comput. Graph. Appl."},{"key":"14_CR23","unstructured":"Ruder, S.: An overview of gradient descent optimization algorithms. arXiv preprint arXiv:1609.04747 (2016)"},{"key":"14_CR24","doi-asserted-by":"publisher","first-page":"45528","DOI":"10.1109\/ACCESS.2021.3066782","volume":"9","author":"S Sadiq","year":"2021","unstructured":"Sadiq, S., et al.: Classification of $$\\beta $$-thalassemia carriers from red blood cell indices using ensemble classifier. IEEE Access 9, 45528\u201345538 (2021)","journal-title":"IEEE Access"},{"key":"14_CR25","doi-asserted-by":"crossref","unstructured":"Santra, B., Mukherjee, D.P., Chakrabarti, D.: A non-invasive approach for estimation of hemoglobin analyzing blood flow in palm. In: 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017), pp. 1100\u20131103. IEEE (2017)","DOI":"10.1109\/ISBI.2017.7950708"},{"key":"14_CR26","doi-asserted-by":"crossref","unstructured":"Stricker, M.A., Orengo, M.: Similarity of color images. In: Storage and retrieval for image and video databases III, vol. 2420, pp. 381\u2013392. SPiE (1995)","DOI":"10.1117\/12.205308"},{"key":"14_CR27","doi-asserted-by":"crossref","unstructured":"Sun, Y., Ren, Z., Zheng, W.: Research on face recognition algorithm based on image processing. Comput. Intell. Neurosci. 2022 (2022)","DOI":"10.1155\/2022\/9224203"},{"key":"14_CR28","doi-asserted-by":"crossref","unstructured":"Tamir, A., Jahan, C.S., et al.: Detection of anemia from image of the anterior conjunctiva of the eye by image processing and thresholding. In: 2017 IEEE Region 10 Humanitarian Technology Conference (R10-HTC), pp. 697\u2013701. IEEE (2017)","DOI":"10.1109\/R10-HTC.2017.8289053"},{"issue":"1","key":"14_CR29","first-page":"129","volume":"4","author":"P Thawari","year":"2011","unstructured":"Thawari, P., Janwe, N.: CBIR based on color and texture. Int. J. Inf. Technol. Knowl. Manag. 4(1), 129\u2013132 (2011)","journal-title":"Int. J. Inf. Technol. Knowl. Manag."},{"key":"14_CR30","unstructured":"Tieleman, T., Hinton, G.: Lecture 6.5-rmsprop, coursera: neural networks for machine learning. Technical report 6, University of Toronto (2012)"},{"issue":"11","key":"14_CR31","doi-asserted-by":"publisher","first-page":"1323","DOI":"10.1016\/S0167-8655(02)00081-8","volume":"23","author":"A Verikas","year":"2002","unstructured":"Verikas, A., Bacauskiene, M.: Feature selection with neural networks. Pattern Recogn. Lett. 23(11), 1323\u20131335 (2002)","journal-title":"Pattern Recogn. Lett."},{"key":"14_CR32","doi-asserted-by":"crossref","unstructured":"Wang, E.J., Li, W., Hawkins, D., Gernsheimer, T., Norby-Slycord, C., Patel, S.N.: HemaApp: noninvasive blood screening of hemoglobin using smartphone cameras. In: Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, pp. 593\u2013604 (2016)","DOI":"10.1145\/2971648.2971653"}],"container-title":["Communications in Computer and Information Science","Computer Vision and Image Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-31417-9_14","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,5,6]],"date-time":"2023-05-06T12:11:42Z","timestamp":1683375102000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-31417-9_14"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031314162","9783031314179"],"references-count":32,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-31417-9_14","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"value":"1865-0929","type":"print"},{"value":"1865-0937","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"7 May 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CVIP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Computer Vision and Image Processing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Nagpur","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"India","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 November 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6 November 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"cvip2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/vnit.ac.in\/cvip2022\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Microsoft CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"307","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"110","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"11","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"36% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}