IP Verse

Method For Controlling A Soil Working Means Based On Image Processing And Related System - EP3629693

The patent EP3629693 was granted to Volta Robots on Jan 26, 2022. The application was originally filed on May 29, 2018 under application number EP18730872A. The patent is currently recorded with a legal status of "Granted And Under Opposition".

EP3629693

VOLTA ROBOTS
Application Number
EP18730872A
Filing Date
May 29, 2018
Status
Granted And Under Opposition
Dec 24, 2021
Grant Date
Jan 26, 2022
External Links
Slate, Register, Google Patents

Patent Summary

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Patent Family

Patent Oppositions (2)

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HUSQVARNAOct 26, 2022SCHROERADMISSIBLE
KILBURN & STRODEOct 26, 2022KORENBERGADMISSIBLE

Patent Citations (32) New

Patent citations refer to prior patents cited during different phases such as opposition or international search.

Citation PhasePublication NumberPublication Link
EXAMINATIONJP2944774B
INTERNATIONAL-SEARCH-REPORTEP2944174
INTERNATIONAL-SEARCH-REPORTJP2944774B
INTERNATIONAL-SEARCH-REPORTUS2014215984
INTERNATIONAL-SEARCH-REPORTUS8412419
OPPOSITIONCN103901890
OPPOSITIONCN104793620
OPPOSITIONEP2286653
OPPOSITIONEP2449532
OPPOSITIONEP2764764
OPPOSITIONEP2944174
OPPOSITIONJP2944774B
OPPOSITIONJPH04293404
OPPOSITIONKR20170011503
OPPOSITIONUS2005102079
OPPOSITIONUS2014215984
OPPOSITIONUS2015027040
OPPOSITIONUS2015306761
OPPOSITIONUS2016148104
OPPOSITIONUS2016375592
OPPOSITIONUS2017024877
OPPOSITIONUS5911669
OPPOSITIONUS8412419
OPPOSITIONUS9008840
OPPOSITIONWO2011002512
OPPOSITIONWO2016097900
OPPOSITIONWO2016103068
OPPOSITIONWO2017049304
OPPOSITIONWO2018075674
OPPOSITIONWO2018087546
OPPOSITIONWO2018208947
OPPOSITIONWO9846065

Non-Patent Literature (NPL) Citations (20) New

NPL citations refer to non-patent references such as research papers, articles, or other publications cited during examination or opposition phases.

Citation PhaseReference TextLink
OPPOSITION- Abhinav Valada, Gabriel.L.Oliveira ,Thomas Brox, Wolfran Burgard , "Robust Semantic Segmentation using Deep Fusion", departement of computer science universitz of freiburg, (20160101), XP055978144-
OPPOSITION- Anonymous, "caffe deconvolution layer ", caffe, (20170428), caffe , URL: http://caffe.berkeleyvision.org/doxyqen/ciasscaffe 1 1DeconvolutionLayer.html, (20221107), XP055978153-
OPPOSITION- Anonymous, "Computer Vision", Wikipedia, (20170515), Wikipedia, (20221107), XP055978136-
OPPOSITION- Anonymous, "Convolutional Neural Network", WIKIPEDIA, (20170220), WIKIPEDIA, (20221107), XP055978154-
OPPOSITION- Anonymous, "Convolutional neural network", wikipedia, (20170522), wikipedia, (20221107), XP055978138-
OPPOSITION- Anonymous, "Embedded visual perception for autonomous lawn mowers using deep Neural Networks for Semantic segmentation", YouTube, (20170120), YouTube, URL: https:/ /www.youtube.com/watch?v=UMIBviZHiYU, (20221107), XP055978143-
OPPOSITION- Anonymous, "Volta Robots al CES2017, la guida autonoma dei veicoli pensata in Italia", macitznet.it, (20170109), XP055978142-
OPPOSITION- Anonymous, "what are deconvolutional layers ", datascience.stackexchanqe.com, (20170223), datascience.stackexchanqe.com, URL: https://datascience.stackexchanqe.com/questions/6107/what-are-deconvolutional-layers, (20221107), XP055978147-
OPPOSITION- Christiansen Peter, Lars N.Nielsen, Kim A. Steen, "Combining Background Subtraction and Deep Learning for Detecting Obstacles and Anomalies in an Agricultural Field", sensors, (20161101), vol. 16, no. 11, XP055978146-
OPPOSITION- Jonathan Long, Evan Shellhamer, Trevor Darrell , "fully convolutional networks for semantic segmentation ", arxiv, (20150308), arxiv, (20221107), XP055978158-
OPPOSITION- Jonghoon Jin, Dundar Aysegul, Culurciello Eugenio, "Flattened Convolutional Neural Networks for Feedforward Acceleration", Arxiv.org, (20151120), pages 1 - 11, Arxiv.org, URL: https://arxiv.org/pdf/1412.5474.pdf, (20200326), XP055679994-
OPPOSITION- Mariusz Bojarski; Davide Del Testa; Daniel Dworakowski; Bernhard Firner; Beat Flepp; Prasoon Goyal; Lawrence D. Jackel; Mathew Monfort; Urs Muller; Jiakai Zhang; Xin Zhang; Jake Zhao; Karol Zieba, "End to End Learning for Self-Driving Cars", arXiv.org, Cornell University Library, 201 Olin Library Cornell University Ithaca, NY 14853, 201 Olin Library Cornell University Ithaca, NY 14853 , (20160425), XP080697746-
OPPOSITION- Rai Piyush, "Deep Learning: Feedforward Neural Nets and Convolutional Neural Nets E15", Machine Learning, (20161102), XP055978145-
OPPOSITION- Vincent Dumoulin; Francesco Visin, "A guide to convolution arithmetic for deep learning", arXiv.org, Cornell University Library, 201 Olin Library Cornell University Ithaca, NY 14853, 201 Olin Library Cornell University Ithaca, NY 14853 , (20160323), XP081351181-
OPPOSITION- Yoshua Bengio, Ian Goodfelllow, Aaron Courville , "chapter 1 ", Deep Learning, (20160101), pages 8 - 247,320-361, XP055978140-
OPPOSITION- Chris Mccool, Et Al., "Mixtures of Lightweight Deep Convolutional Neural Networks: Applied to Agricultural Robotics", IEEE Robotics and Automation Letters, (20170701), vol. 2, no. 3, doi:10.1109/LRA.2017.2667039, pages 1344 - 1351, XP055496006
OPPOSITION- Guo Yao, Sun Fu-Chun, "Vision-based Lawn Boundary Recognition for Mowing Robot", Proceedings of the 2016 International Conference on Computer Engineering and Information Systems, Atlantis Press, Paris, France, Paris, France, (20160101), doi:10.2991/ceis-16.2016.16, ISBN 978-94-625-2283-1, XP055978134
OPPOSITION- Steen Kim, Christiansen Peter, Karstoft Henrik, Jørgensen Rasmus, "Using Deep Learning to Challenge Safety Standard for Highly Autonomous Machines in Agriculture", Journal of Imaging, (20160215), vol. 2, no. 1, doi:10.3390/jimaging2010006, page 6, XP055978139
OPPOSITION- Inkyu Sa, Ge Zongyuan, Dayoub Feras, Upcroft Ben, Perez Tristan, Mccool Chris, "DeepFruits: A Fruit Detection System Using Deep Neural Networks", Sensors, (20160803), vol. 16, no. 8, doi:10.3390/s16081222, pages 1 - 23, XP055469740
OPPOSITION- Christiansen Peter, Nielsen Lars, Steen Kim, Jørgensen Rasmus, Karstoft Henrik, "DeepAnomaly: Combining Background Subtraction and Deep Learning for Detecting Obstacles and Anomalies in an Agricultural Field", Sensors, (20161111), vol. 16, no. 11, doi:10.3390/s16111904, page 1904, XP055978137

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