{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,2]],"date-time":"2026-03-02T11:07:41Z","timestamp":1772449661255,"version":"3.50.1"},"publisher-location":"Singapore","reference-count":22,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819699131","type":"print"},{"value":"9789819699148","type":"electronic"}],"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\/978-981-96-9914-8_35","type":"book-chapter","created":{"date-parts":[[2025,7,16]],"date-time":"2025-07-16T14:23:57Z","timestamp":1752675837000},"page":"420-431","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["AMC-Net: Adaptive Multi-channel Sampling and Deep Reconstruction for Block-Based Image Compressive Sensing"],"prefix":"10.1007","author":[{"given":"Yi","family":"Zhen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Banglv","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yufeng","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hui","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,7,17]]},"reference":[{"issue":"4","key":"35_CR1","doi-asserted-by":"publisher","first-page":"1289","DOI":"10.1109\/TIT.2006.871582","volume":"52","author":"DL Donoho","year":"2006","unstructured":"Donoho, D.L.: Compressed sensing. IEEE Trans. Inf. Theory 52(4), 1289\u20131306 (2006)","journal-title":"IEEE Trans. Inf. Theory"},{"key":"35_CR2","doi-asserted-by":"crossref","unstructured":"Sankaranarayanan, A.C., Studer, C., Baraniuk, R.G.: CS-MUVI: video compressive sensing for spatial-multiplexing cameras. In: 2012 IEEE International Conference on Computational Photography (ICCP), pp. 1\u201310. IEEE, Seattle, WA, USA (2012)","DOI":"10.1109\/ICCPhot.2012.6215212"},{"issue":"2","key":"35_CR3","doi-asserted-by":"publisher","first-page":"83","DOI":"10.1109\/MSP.2007.914730","volume":"25","author":"MF Duarte","year":"2008","unstructured":"Duarte, M.F., Davenport, M.A., Takhar, D., et al.: Single-pixel imaging via compressive sampling. IEEE Signal Process. Mag. 25(2), 83\u201391 (2008)","journal-title":"IEEE Signal Process. Mag."},{"issue":"10","key":"35_CR4","doi-asserted-by":"publisher","first-page":"2148","DOI":"10.1109\/TMI.2017.2717502","volume":"36","author":"Y Liu","year":"2017","unstructured":"Liu, Y., Wu, S., Huang, X., Chen, B., Zhu, C.: Hybrid CS-DMRI: periodic time-variant subsampling and omnidirectional total variation based reconstruction. IEEE Trans. Med. Imaging 36(10), 2148\u20132159 (2017)","journal-title":"IEEE Trans. Med. Imaging"},{"issue":"3","key":"35_CR5","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1109\/MSP.2012.2183771","volume":"29","author":"E Axell","year":"2012","unstructured":"Axell, E., Leus, G., Larsson, E.G., Poor, H.V.: Spectrum sensing for cognitive radio: state-of-the-art and recent advances. IEEE Signal Process. Mag. 29(3), 101\u2013116 (2012)","journal-title":"IEEE Signal Process. Mag."},{"issue":"12","key":"35_CR6","doi-asserted-by":"publisher","first-page":"1983","DOI":"10.1109\/TMC.2011.216","volume":"11","author":"C Feng","year":"2012","unstructured":"Feng, C., Au, W.S.A., Valaee, S., et al.: Received-signal-strength-based indoor positioning using compressive sensing. IEEE Trans. Mob. Comput. 11(12), 1983\u20131993 (2012)","journal-title":"IEEE Trans. Mob. Comput."},{"issue":"46\u201347","key":"35_CR7","first-page":"4","volume":"20","author":"C Li","year":"2009","unstructured":"Li, C., Yin, W., Zhang, Y.: User\u2019s guide for TVAL3: TV minimization by augmented lagrangian and alternating direction algorithms. CAAM Report 20(46\u201347), 4 (2009)","journal-title":"CAAM Report"},{"key":"35_CR8","doi-asserted-by":"crossref","unstructured":"Kulkarni, K., Lohit, S., Turaga, P., et al.: ReconNet: non-iterative reconstruction of images from compressively sensed measurements. In: Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR), pp. 449\u2013458. IEEE (2016)","DOI":"10.1109\/CVPR.2016.55"},{"key":"35_CR9","doi-asserted-by":"crossref","unstructured":"Zhang, J., Ghanem, B.: ISTA-Net: interpretable optimization-inspired deep network for image compressive sensing. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1828\u20131837. IEEE (2018)","DOI":"10.1109\/CVPR.2018.00196"},{"key":"35_CR10","doi-asserted-by":"crossref","unstructured":"Shi, W., Jiang, F., Liu, S., et al.: Scalable convolutional neural network for image compressed sensing. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12290\u201312299. IEEE (2019)","DOI":"10.1109\/CVPR.2019.01257"},{"key":"35_CR11","doi-asserted-by":"publisher","first-page":"375","DOI":"10.1109\/TIP.2019.2928136","volume":"29","author":"W Shi","year":"2019","unstructured":"Shi, W., Jiang, F., Liu, S., et al.: Image compressed sensing using convolutional neural network. IEEE Trans. Image Process. 29, 375\u2013388 (2019)","journal-title":"IEEE Trans. Image Process."},{"issue":"4","key":"35_CR12","doi-asserted-by":"publisher","first-page":"765","DOI":"10.1109\/JSTSP.2020.2977507","volume":"14","author":"J Zhang","year":"2020","unstructured":"Zhang, J., Zhao, C., Gao, W.: Optimization-inspired compact deep compressive sensing. IEEE J. Sel. Top. Signal Process. 14(4), 765\u2013774 (2020)","journal-title":"IEEE J. Sel. Top. Signal Process."},{"key":"35_CR13","doi-asserted-by":"publisher","first-page":"1487","DOI":"10.1109\/TIP.2020.3044472","volume":"30","author":"Z Zhang","year":"2020","unstructured":"Zhang, Z., Liu, Y., Liu, J., et al.: AMP-net: denoising-based deep unfolding for compressive image sensing. IEEE Trans. Image Process. 30, 1487\u20131500 (2020)","journal-title":"IEEE Trans. Image Process."},{"key":"35_CR14","doi-asserted-by":"crossref","unstructured":"Shen, M., Gan, H., Ma, C., et al.: MTC-CSNet: marrying transformer and convolution for image compressed sensing. IEEE Trans. Cybern. (2024)","DOI":"10.1109\/TCYB.2024.3363748"},{"issue":"5","key":"35_CR15","doi-asserted-by":"publisher","first-page":"2974","DOI":"10.1109\/TSC.2023.3334446","volume":"17","author":"K Zhang","year":"2023","unstructured":"Zhang, K., Hua, Z., Li, Y., et al.: Uformer-ICS: a U-shaped transformer for image compressive sensing service. IEEE Trans. Serv. Comput. 17(5), 2974\u20132988 (2023)","journal-title":"IEEE Trans. Serv. Comput."},{"key":"35_CR16","doi-asserted-by":"publisher","first-page":"2515","DOI":"10.1109\/TMM.2023.3301213","volume":"26","author":"C Hui","year":"2023","unstructured":"Hui, C., Zhang, S., Cui, W., et al.: Rate-adaptive neural network for image compressive sensing. IEEE Trans. Multimed. 26, 2515\u20132530 (2023)","journal-title":"IEEE Trans. Multimed."},{"key":"35_CR17","doi-asserted-by":"publisher","first-page":"2627","DOI":"10.1109\/TMM.2020.3014561","volume":"23","author":"S Zhou","year":"2020","unstructured":"Zhou, S., He, Y., Liu, Y., et al.: Multi-channel deep networks for block-based image compressive sensing. IEEE Trans. Multimed. 23, 2627\u20132640 (2020)","journal-title":"IEEE Trans. Multimed."},{"key":"35_CR18","doi-asserted-by":"publisher","first-page":"6991","DOI":"10.1109\/TIP.2022.3217365","volume":"31","author":"M Shen","year":"2022","unstructured":"Shen, M., Gan, H., Ning, C., et al.: TransCS: a transformer-based hybrid architecture for image compressed sensing. IEEE Trans. Image Process. 31, 6991\u20137005 (2022)","journal-title":"IEEE Trans. Image Process."},{"key":"35_CR19","doi-asserted-by":"publisher","first-page":"2827","DOI":"10.1109\/TIP.2023.3274988","volume":"32","author":"D Ye","year":"2023","unstructured":"Ye, D., Ni, Z., Wang, H., et al.: CSformer: bridging convolution and transformer for compressive sensing. IEEE Trans. Image Process. 32, 2827\u20132842 (2023)","journal-title":"IEEE Trans. Image Process."},{"key":"35_CR20","doi-asserted-by":"publisher","first-page":"5412","DOI":"10.1109\/TIP.2022.3195319","volume":"31","author":"B Chen","year":"2022","unstructured":"Chen, B., Zhang, J.: Content-aware scalable deep compressed sensing. IEEE Trans. Image Process. 31, 5412\u20135426 (2022)","journal-title":"IEEE Trans. Image Process."},{"issue":"6","key":"35_CR21","doi-asserted-by":"publisher","first-page":"155014771878175","DOI":"10.1177\/1550147718781751","volume":"14","author":"R Li","year":"2018","unstructured":"Li, R., Duan, X., Lv, Y.: Adaptive compressive sensing of images using error between blocks. Int. J. Distrib. Sens. Netw. 14(6), 1550147718781751 (2018)","journal-title":"Int. J. Distrib. Sens. Netw."},{"key":"35_CR22","doi-asserted-by":"publisher","first-page":"5676","DOI":"10.1109\/TMM.2022.3198323","volume":"25","author":"K Zhang","year":"2022","unstructured":"Zhang, K., Hua, Z., Li, Y., et al.: AMS-Net: adaptive multi-scale network for image compressive sensing. IEEE Trans. Multimed. 25, 5676\u20135689 (2022)","journal-title":"IEEE Trans. Multimed."}],"container-title":["Lecture Notes in Computer Science","Advanced Intelligent Computing Technology and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-96-9914-8_35","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,2]],"date-time":"2026-03-02T10:39:34Z","timestamp":1772447974000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-96-9914-8_35"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9789819699131","9789819699148"],"references-count":22,"URL":"https:\/\/doi.org\/10.1007\/978-981-96-9914-8_35","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"17 July 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Ningbo","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":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 July 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 July 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icic2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ic-icc.cn\/icg\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}