{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T04:22:37Z","timestamp":1742962957379,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":30,"publisher":"Springer Singapore","isbn-type":[{"type":"print","value":"9789813297661"},{"type":"electronic","value":"9789813297678"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-981-32-9767-8_42","type":"book-chapter","created":{"date-parts":[[2019,8,17]],"date-time":"2019-08-17T02:02:54Z","timestamp":1566007374000},"page":"510-522","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Real Time Implementation of Convolutional Neural Network to Detect Plant Diseases Using Internet of Things"],"prefix":"10.1007","author":[{"given":"Govind","family":"Bajpai","sequence":"first","affiliation":[]},{"given":"Aniket","family":"Gupta","sequence":"additional","affiliation":[]},{"given":"Nitanshu","family":"Chauhan","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,8,18]]},"reference":[{"key":"42_CR1","volume-title":"C4. 5: Programs for Machine Learning","author":"JR Quinlan","year":"2014","unstructured":"Quinlan, J.R.: C4. 5: Programs for Machine Learning. Elsevier, Amsterdam (2014)"},{"key":"42_CR2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/B978-0-12-407684-6.00031-0","volume-title":"From Machine-to-Machine to the Internet of Things","author":"J H\u00f6ller","year":"2014","unstructured":"H\u00f6ller, J., Boyle, D., Karnouskos, S., Avesand, S., Mulligan, C., Tsiatsis, V.: From Machine-to-Machine to the Internet of Things, pp. 1\u2013331. Academic Press, Cambridge (2014)"},{"key":"42_CR3","volume-title":"Principles of Artificial Intelligence","author":"NJ Nilsson","year":"2014","unstructured":"Nilsson, N.J.: Principles of Artificial Intelligence. Morgan Kaufmann, Burlington (2014)"},{"issue":"4","key":"42_CR4","doi-asserted-by":"publisher","first-page":"76","DOI":"10.1038\/scientificamerican1004-76","volume":"291","author":"N Gershenfeld","year":"2004","unstructured":"Gershenfeld, N., Krikorian, R., Cohen, D.: The Internet of Things. Sci. Am. 291(4), 76\u201381 (2004)","journal-title":"Sci. Am."},{"key":"42_CR5","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"525","DOI":"10.1007\/978-3-319-46493-0_32","volume-title":"Computer Vision \u2013 ECCV 2016","author":"M Rastegari","year":"2016","unstructured":"Rastegari, M., Ordonez, V., Redmon, J., Farhadi, A.: XNOR-Net: imagenet classification using binary convolutional neural networks. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9908, pp. 525\u2013542. Springer, Cham (2016). \n                    https:\/\/doi.org\/10.1007\/978-3-319-46493-0_32"},{"key":"42_CR6","volume-title":"An Introduction to Neural Networks","author":"A Anderson","year":"1998","unstructured":"Anderson, A.: An Introduction to Neural Networks. PHI Publication, Amsterdam (1998)"},{"key":"42_CR7","unstructured":"Cire\u015fan, D.C., Meier, U., Masci, J., Gambardella, L.M., Schmidhuber, J.: High-performance neural networks for visual object classification. Arxiv preprint \n                    arXiv:1102.0183\n                    \n                   (2011)"},{"key":"42_CR8","doi-asserted-by":"crossref","unstructured":"Szegedy, C., et al.: Going deeper with convolutions. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1\u20139 (2015)","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"42_CR9","unstructured":"Gomez, R., Gomez, L., Gibert, J., Karatzas, D.: Self-Supervised Learning from Web Data for Multimodal Retrieval. arXiv preprint \n                    arXiv:1901.02004"},{"key":"42_CR10","unstructured":"Iandola, F.N., Han, S., Moskewicz, M.W., Ashraf, K., Dally, W.J., Keutzer, K.: SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and\u2009<0.5 mb model size. arXiv preprint \n                    arXiv:1602.07360\n                    \n                   (2016)"},{"key":"42_CR11","doi-asserted-by":"crossref","unstructured":"Yuan, Z.W., Zhang, J.: Feature extraction and image retrieval based on AlexNet. In: Eighth International Conference on Digital Image Processing, ICDIP 2016, vol. 10033, p. 100330E. International Society for Optics and Photonics (2016)","DOI":"10.1117\/12.2243849"},{"key":"42_CR12","doi-asserted-by":"crossref","unstructured":"Singla, A., Yuan, L., Ebrahimi, T.: Food\/non-food image classification and food categorization using pre-trained googlenet model. In: Proceedings of the 2nd International Workshop on Multimedia Assisted Dietary Management, pp. 3\u201311. ACM (2016)","DOI":"10.1145\/2986035.2986039"},{"key":"42_CR13","doi-asserted-by":"publisher","first-page":"188","DOI":"10.1016\/j.neucom.2016.11.023","volume":"225","author":"P Tang","year":"2017","unstructured":"Tang, P., Wang, H., Kwong, S.: G-MS2F: GoogLeNet based multi-stage feature fusion of deep CNN for scene recognition. Neurocomputing 225, 188\u2013197 (2017)","journal-title":"Neurocomputing"},{"key":"42_CR14","first-page":"19","volume":"90","author":"Z Wu","year":"2019","unstructured":"Wu, Z., Shen, C., Van Den Hengel, A.: Wider or deeper: revisiting the resnet model for visual recognition. Pattern Recognit. 90, 19\u2013133 (2019)","journal-title":"Pattern Recognit."},{"key":"42_CR15","unstructured":"Xia, X., Xu, C., Nan, B.: Inception-v3 for flower classification. In: 2017 2nd International Conference on Image, Vision and Computing (ICIVC), pp. 783\u2013787. IEEE (2017)"},{"key":"42_CR16","unstructured":"Barratt, S., Sharma, R.: A note on the inception score. arXiv preprint \n                    arXiv:1801.01973\n                    \n                   (2018)"},{"issue":"1","key":"42_CR17","first-page":"41","volume":"4","author":"V Singh","year":"2017","unstructured":"Singh, V., Misra, A.K.: Detection of plant leaf diseases using image segmentation and soft computing techniques. Inf. Process. Agric. 4(1), 41\u201349 (2017)","journal-title":"Inf. Process. Agric."},{"key":"42_CR18","doi-asserted-by":"publisher","first-page":"1419","DOI":"10.3389\/fpls.2016.01419","volume":"7","author":"SP Mohanty","year":"2016","unstructured":"Mohanty, S.P., Hughes, D.P., Salath\u00e9, M.: Using deep learning for image-based plant disease detection. Front. Plant Sci. 7, 1419 (2016)","journal-title":"Front. Plant Sci."},{"key":"42_CR19","unstructured":"Available online: \n                    plantvillage.psu.edu"},{"key":"42_CR20","doi-asserted-by":"crossref","unstructured":"Sladojevic, S., Arsenovic, M., Anderla, A., Culibrk, D., Stefanovic, D.: Deep neural networks based recognition of plant diseases by leaf image classification. In: Computational Intelligence and Neuroscience (2016)","DOI":"10.1155\/2016\/3289801"},{"key":"42_CR21","doi-asserted-by":"publisher","first-page":"84","DOI":"10.1016\/j.biosystemseng.2018.05.013","volume":"172","author":"JG Barbedo","year":"2018","unstructured":"Barbedo, J.G.: Factors influencing the use of deep learning for plant disease recognition. Biosyst. Eng. 172, 84\u201391 (2018)","journal-title":"Biosyst. Eng."},{"key":"42_CR22","doi-asserted-by":"publisher","first-page":"311","DOI":"10.1016\/j.compag.2018.01.009","volume":"145","author":"KP Ferentinos","year":"2018","unstructured":"Ferentinos, K.P.: Deep learning models for plant disease detection and diagnosis. Comput. Electron. Agric. 145, 311\u2013318 (2018)","journal-title":"Comput. Electron. Agric."},{"issue":"7","key":"42_CR23","doi-asserted-by":"publisher","first-page":"1497","DOI":"10.1016\/j.adhoc.2012.02.016","volume":"10","author":"D Miorandi","year":"2012","unstructured":"Miorandi, D., Sicari, S., De Pellegrini, F., Chlamtac, I.: Internet of Things: vision, applications and research challenges. Ad Hoc Netw. 10(7), 1497\u20131516 (2012)","journal-title":"Ad Hoc Netw."},{"issue":"1","key":"42_CR24","doi-asserted-by":"publisher","first-page":"22","DOI":"10.1109\/JIOT.2014.2306328","volume":"1","author":"A Zanella","year":"2014","unstructured":"Zanella, A., Bui, N., Castellani, A., Vangelista, L., Zorzi, M.: Internet of things for smart cities. IEEE Internet Things J. 1(1), 22\u201332 (2014)","journal-title":"IEEE Internet Things J."},{"key":"42_CR25","doi-asserted-by":"crossref","unstructured":"Mohammed, J., Lung, C.H., Ocneanu, A., Thakral, A., Jones, C., Adler, A.: Internet of Things: remote patient monitoring using web services and cloud computing. In: 2014 IEEE International Conference on Internet of things (iThings) and Green Computing and Communications (GreenCom), IEEE and Cyber, Physical and Social Computing (CPSCom), pp. 256\u2013263. IEEE (2014)","DOI":"10.1109\/iThings.2014.45"},{"key":"42_CR26","doi-asserted-by":"crossref","unstructured":"Vattapparamban, E., G\u00fcven\u00e7, \u0130., Yurekli, A.\u0130., Akkaya, K., Ulua\u011fa\u00e7, S.: Drones for smart cities: issues in cybersecurity, privacy, and public safety. In: 2016 International Wireless Communications and Mobile computing Conference (IWCMC), pp. 216\u2013221. IEEE (2016)","DOI":"10.1109\/IWCMC.2016.7577060"},{"key":"42_CR27","unstructured":"Dang, C.T., Pham, H.T., Pham, T.B., Truong, N.V.: Vision based ground object tracking using AR. Drone quadrotor. In: 2013 International Conference on Control, Automation and Information Sciences (ICCAIS), pp. 146\u2013151. IEEE (2013)"},{"key":"42_CR28","unstructured":"www.pwc.be\/en\/documents\/20180518-drone-study.pdf"},{"key":"42_CR29","unstructured":"Reitermanova, Z.: Data splitting. In: WDS, vol. 10, pp. 31\u201336 (2010)"},{"key":"42_CR30","unstructured":"www.openmv.io\/"}],"container-title":["Communications in Computer and Information Science","VLSI Design and Test"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-32-9767-8_42","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,9,12]],"date-time":"2019-09-12T02:07:19Z","timestamp":1568254039000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-981-32-9767-8_42"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9789813297661","9789813297678"],"references-count":30,"URL":"https:\/\/doi.org\/10.1007\/978-981-32-9767-8_42","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"18 August 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"VDAT","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Symposium on VLSI Design and Test","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Indore","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":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 July 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6 July 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"vdat2019a","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/vdat2019.iiti.ac.in\/","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":"Easychair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"199","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":"63","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":"32% - 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":"-","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":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}