{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T16:46:06Z","timestamp":1742921166051,"version":"3.40.3"},"publisher-location":"Cham","reference-count":18,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031463341"},{"type":"electronic","value":"9783031463358"}],"license":[{"start":{"date-parts":[[2023,11,5]],"date-time":"2023-11-05T00:00:00Z","timestamp":1699142400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,11,5]],"date-time":"2023-11-05T00:00:00Z","timestamp":1699142400000},"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":[[2024]]},"DOI":"10.1007\/978-3-031-46335-8_4","type":"book-chapter","created":{"date-parts":[[2023,11,4]],"date-time":"2023-11-04T17:02:05Z","timestamp":1699117325000},"page":"38-51","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Enhancing Image Quality of Aging Smartphones Using Multi-scale Selective Kernel Feature Fusion Network"],"prefix":"10.1007","author":[{"given":"Md. Yearat","family":"Hossain","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Md. Mahbub Hasan","family":"Rakib","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ifran Rahman","family":"Nijhum","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tanzilur","family":"Rahman","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,11,5]]},"reference":[{"key":"4_CR1","unstructured":"How Many Photos Are There? 50+ Photos Statistics (2023). https:\/\/photutorial.com\/photos-statistics\/. Accessed 14 Jan 2023"},{"key":"4_CR2","unstructured":"Lee, J., et al.: On-device neural net inference with mobile GPUs. arXiv preprint arXiv:1907.01989 (2019)"},{"key":"4_CR3","doi-asserted-by":"crossref","unstructured":"Guo, C., et al.: Zero-reference deep curve estimation for low-light image enhancement. In: IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1780\u20131789 (2020)","DOI":"10.1109\/CVPR42600.2020.00185"},{"key":"4_CR4","doi-asserted-by":"publisher","first-page":"9540","DOI":"10.1109\/ACCESS.2020.2964823","volume":"8","author":"Y Kinoshita","year":"2020","unstructured":"Kinoshita, Y., Kiya, H.: Hue-correction scheme based on constant-hue plane for deep-learning-based color-image enhancement. IEEE Access 8, 9540\u20139550 (2020)","journal-title":"IEEE Access"},{"key":"4_CR5","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"197","DOI":"10.1007\/978-3-030-11021-5_13","volume-title":"Computer Vision \u2013 ECCV 2018 Workshops","author":"Z Hui","year":"2019","unstructured":"Hui, Z., Wang, X., Deng, L., Gao, X.: Perception-preserving convolutional networks for image enhancement on smartphones. In: Leal-Taix\u00e9, L., Roth, S. (eds.) ECCV 2018. LNCS, vol. 11133, pp. 197\u2013213. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-11021-5_13"},{"key":"4_CR6","unstructured":"Ignatov, A., et al.: PIRM challenge on perceptual image enhancement on smartphones: Report. In: European Conference on Computer Vision (ECCV) Workshops (2018)"},{"key":"4_CR7","doi-asserted-by":"crossref","unstructured":"Engin, D., Genc, A., Kemal Ekenel, H.: Cycle-dehaze: enhanced CycleGAN for single image dehazing. In: IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 825\u2013833 (2018)","DOI":"10.1109\/CVPRW.2018.00127"},{"key":"4_CR8","doi-asserted-by":"crossref","unstructured":"Kuanar, S., Mahapatra, D., Bilas, M., Rao, K.R.: Multi-path dilated convolution network for haze and glow removal in nighttime images. In: Visual Computer, pp. 1\u201314 (2022)","DOI":"10.1007\/s00371-021-02071-z"},{"key":"4_CR9","doi-asserted-by":"crossref","unstructured":"Burger, H.C., Schuler, C.J., Harmeling, S.: Image denoising: can plain neural networks compete with BM3D? In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2392\u20132399 (2012)","DOI":"10.1109\/CVPR.2012.6247952"},{"key":"4_CR10","unstructured":"Shen, L., Yue, Z., Feng, F., Chen, Q., Liu, S., Ma, J.: MSR-net: low-light image enhancement using deep convolutional network. arXiv preprint arXiv:1711.02488 (2017)"},{"key":"4_CR11","doi-asserted-by":"publisher","first-page":"650","DOI":"10.1016\/j.patcog.2016.06.008","volume":"61","author":"KG Lore","year":"2017","unstructured":"Lore, K.G., Akintayo, A., Sarkar, S.: LLNet: a deep autoencoder approach to natural low-light image enhancement. Pattern Recogn. 61, 650\u2013662 (2017)","journal-title":"Pattern Recogn."},{"key":"4_CR12","doi-asserted-by":"publisher","first-page":"14363","DOI":"10.1007\/s11042-020-10310-z","volume":"80","author":"L Yan","year":"2021","unstructured":"Yan, L., Fu, J., Wang, C., Ye, Z., Chen, H., Ling, H.: Enhanced network optimized generative adversarial network for image enhancement. Multimedia Tools Appl. 80, 14363\u201314381 (2021)","journal-title":"Multimedia Tools Appl."},{"key":"4_CR13","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"492","DOI":"10.1007\/978-3-030-58595-2_30","volume-title":"Computer Vision \u2013 ECCV 2020","author":"SW Zamir","year":"2020","unstructured":"Zamir, S.W., et al.: Learning enriched features for real image restoration and enhancement. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.-M. (eds.) ECCV 2020. LNCS, vol. 12370, pp. 492\u2013511. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58595-2_30"},{"key":"4_CR14","doi-asserted-by":"crossref","unstructured":"Charbonnier, P., Blanc-F\u00e9raud, L., Aubert, G., Barlaud, M.: Two deterministic half-quadratic regularization algorithms for computed imaging. In: 1st International Conference on Image Processing, vol. 2, pp. 168\u2013172 (1994)","DOI":"10.1109\/ICIP.1994.413553"},{"key":"4_CR15","unstructured":"GIMP - GNU Image Manipulation Program. https:\/\/www.gimp.org\/. Accessed 24 Feb 2023"},{"key":"4_CR16","unstructured":"Kumar, J., Chen, F., Doermann, D.: Sharpness estimation for document and scene images. In: 21st International Conference on Pattern Recognition (ICPR 2012), pp. 3292\u20133295 (2012)"},{"key":"4_CR17","doi-asserted-by":"crossref","unstructured":"Su, S., et al.: Blindly assess image quality in the wild guided by a self-adaptive hyper network. In: IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3667\u20133676 (2020)","DOI":"10.1109\/CVPR42600.2020.00372"},{"key":"4_CR18","doi-asserted-by":"publisher","first-page":"4041","DOI":"10.1109\/TIP.2020.2967829","volume":"29","author":"V Hosu","year":"2020","unstructured":"Hosu, V., Lin, H., Sziranyi, T., Saupe, D.: KonIQ-10k: an ecologically valid database for deep learning of blind image quality assessment. IEEE Trans. Image Process. 29, 4041\u20134056 (2020)","journal-title":"IEEE Trans. Image Process."}],"container-title":["Communications in Computer and Information Science","Intelligent Systems and Pattern Recognition"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-46335-8_4","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,1]],"date-time":"2024-11-01T11:16:28Z","timestamp":1730459788000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-46335-8_4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,11,5]]},"ISBN":["9783031463341","9783031463358"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-46335-8_4","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2023,11,5]]},"assertion":[{"value":"5 November 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ISPR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Systems and Pattern Recognition","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Hammamet","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Tunisia","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 May 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 May 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ispr22023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ispr2023.sciencesconf.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"129","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":"44","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":"0","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":"34% - 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":"3","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)"}}]}}