{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,30]],"date-time":"2025-08-30T16:26:24Z","timestamp":1756571184990,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":21,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819619030"},{"type":"electronic","value":"9789819619047"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"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":[[2025]]},"DOI":"10.1007\/978-981-96-1904-7_7","type":"book-chapter","created":{"date-parts":[[2025,2,23]],"date-time":"2025-02-23T21:24:03Z","timestamp":1740345843000},"page":"73-82","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Performance Analysis of Image Augmentation Driven by Language Based on Diffusion Models"],"prefix":"10.1007","author":[{"given":"Wei","family":"Chen","sequence":"first","affiliation":[]},{"given":"Peng","family":"Zhou","sequence":"additional","affiliation":[]},{"given":"Lina","family":"He","sequence":"additional","affiliation":[]},{"given":"Huan","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Bingyu","family":"Cao","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,2,24]]},"reference":[{"key":"7_CR1","doi-asserted-by":"crossref","unstructured":"Frid-Adar, M., et al.: GAN-based synthetic medical image augmentation for increased CNN performance in liver lesion classification. Neurocomputing 321(DEC.10), 321\u2013331 (2018)","DOI":"10.1016\/j.neucom.2018.09.013"},{"key":"7_CR2","doi-asserted-by":"crossref","unstructured":"Gaudio, A., Smailagic, A.: Aur\u00e9lio Campilho. Enhancement of retinal fundus images via pixel color amplification (2020)","DOI":"10.1007\/978-3-030-50516-5_26"},{"key":"7_CR3","doi-asserted-by":"crossref","unstructured":"Li, H., Liu, H., Hu ,Y., et al.: An annotation-free restoration network for cataractous fundus images (2022)","DOI":"10.1109\/TMI.2022.3147854"},{"key":"7_CR4","unstructured":"Chen, N., Zhang, Y., Zen, H., et al.: WaveGrad: estimating gradients for waveform generation. In: International Conference on Learning Representations (2021)"},{"key":"7_CR5","doi-asserted-by":"crossref","unstructured":"Li, C., Guo, C., Han, L., et al.: Low-light image and video enhancement using deep learning: a survey. IEEE Trans. Pattern Anal. Mach. Intell. 44(12), 9396\u20139416 (2022)","DOI":"10.1109\/TPAMI.2021.3126387"},{"key":"7_CR6","doi-asserted-by":"crossref","unstructured":"Zhang, L., Zhang, Q., Xiao, C.: Shadow remover:image shadow removal based on illumination recovering optimization. IEEE Trans. Image Proces. 24(11), 4623\u20134636 (2015)","DOI":"10.1109\/TIP.2015.2465159"},{"key":"7_CR7","doi-asserted-by":"crossref","unstructured":"Li, C., Guo, J., Porikli, F., et al.: Lightennet: a convolutional neural network for weakly illuminated image enhancement. Pattern Recogn. Let. 104, 15\u201322 (2018)","DOI":"10.1016\/j.patrec.2018.01.010"},{"key":"7_CR8","doi-asserted-by":"crossref","unstructured":"Kim,Y.T.: Contrast enhancement using brightness preserving bi-histogram equalization. IEEE Trans. Consumer Electron. 43(1), 1\u20138 (1997)","DOI":"10.1109\/30.580378"},{"key":"7_CR9","doi-asserted-by":"crossref","unstructured":"Yao, Z., Lai, Z., Wang, C.: Image enhancement based on equal area dualistic sub-image and non-parametric modified histogram equalization method. IEEE (2016)","DOI":"10.1109\/ISCID.2016.1110"},{"key":"7_CR10","unstructured":"Dela\u010d, K.; Grgi\u0107, K.M., et al.: Sub-image homomorphic filtering technique for improving facial identification under difficult illumination conditions. In: International Conference on Systems (2024)"},{"key":"7_CR11","doi-asserted-by":"crossref","unstructured":"Xiao, L., Li, C., Wu, Z., et al.: An enhancement method for X-ray image via fuzzy noise removal and homomorphic filtering. Neurocomputing 56\u201364 (2016)","DOI":"10.1016\/j.neucom.2015.08.113"},{"key":"7_CR12","doi-asserted-by":"crossref","unstructured":"Zhuang, J., Hou, C., Tang, Y., et al.: Computer vision-based localisation of picking points for automatic litchi harvesting applications towards natural scenarios. Biosyst. Eng. 187, 1\u201320 (2019)","DOI":"10.1016\/j.biosystemseng.2019.08.016"},{"key":"7_CR13","doi-asserted-by":"crossref","unstructured":"Jobson, D.J., Rahman, Z., Woodell, G.A.: A multiscale retinex for bridging the gap between color images and the human observation of scenes. IEEE Trans. Image Process. 6(7), 965\u2013976 (2002)","DOI":"10.1109\/83.597272"},{"key":"7_CR14","doi-asserted-by":"crossref","unstructured":"Jiang, Y., Gong, X., Liu, D., et al.: EnlightenGAN: deep light enhancement without paired supervision. IEEE Trans. Image Proces. 30, 2340\u20132349 (2021)","DOI":"10.1109\/TIP.2021.3051462"},{"key":"7_CR15","unstructured":"Hai, J., Xuan, Z., Yang, R., et al.: R2RNet: low-light image enhancement via real-low to real-normal network (2021)"},{"key":"7_CR16","unstructured":"Guo, X., Li, Y., Ling, H.: LIME: low-light image enhancement via illumination map estimation. IEEE Trans. Image Proces. (99), 1\u20131 (2016)"},{"key":"7_CR17","doi-asserted-by":"crossref","unstructured":"Arif, A., Li, T., Cheng, C.H.: Blurred fingerprint image enhancement: algorithm analysis and performance evaluation. Signal Image Video Proces. (2017)","DOI":"10.1007\/s11760-017-1218-0"},{"key":"7_CR18","doi-asserted-by":"crossref","unstructured":"Kapil, D.: Abhilasha Face recognition of blurred images using image enhancement and texture features. IEEE, pp. 894\u2013897 (2015)","DOI":"10.1109\/NGCT.2015.7375248"},{"key":"7_CR19","unstructured":"Kingma, D.P., Welling, M.: Auto-encoding variational bayes. arXiv.org (2014)"},{"key":"7_CR20","unstructured":"Radford, A., Metz, L., Chintala, S.: Unsupervised representation learning with deep convolutional generative adversarial networks. Comput. Sci. 10\u201323 (2015)"},{"key":"7_CR21","first-page":"79024","volume":"36","author":"L Dunlap","year":"2023","unstructured":"Dunlap, L., Umino, A., Zhang, H., et al.: Diversify your vision datasets with automatic diffusion-based augmentation. Adv. Neural. Inf. Process. Syst. 36, 79024\u201379034 (2023)","journal-title":"Adv. Neural. Inf. Process. Syst."}],"container-title":["Communications in Computer and Information Science","Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-96-1904-7_7","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,23]],"date-time":"2025-02-23T21:24:13Z","timestamp":1740345853000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-96-1904-7_7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9789819619030","9789819619047"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-981-96-1904-7_7","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"24 February 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICAI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Applied Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Zhenzhou","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 November 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25 November 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icai12024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/icai.org.cn\/2024\/Organization.php","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}