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Mechanik, Maschinenbau","publisher":"Teubner","address":"Stuttgart", "year": "1990", "url": "", "editor": [ "Jochem [Verfasser/in] Unger" ], "editors": [ {"first" : "Jochem [Verfasser/in]", "last" : "Unger"} ], "isbn" : "3-519-00140-3", "language" : "Deutsch", "bibtexKey": "unger_einfuhrung_1990" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/29f3ea1a58a5a753e57bb6dc296802198/felixholm", "tags" : [ "annotation","automatic","cataract","challenge","dataset","surgery","tool" ], "intraHash" : "9f3ea1a58a5a753e57bb6dc296802198", "interHash" : "c477e5d427734d2fdcee92e0fe2bca8d", "label" : "CATARACTS: Challenge on automatic tool annotation for cataRACT surgery", "user" : "felixholm", "description" : "CATARACTS: Challenge on automatic tool annotation for cataRACT surgery - ScienceDirect", "date" : "2021-08-07 22:52:08", "changeDate" : "2021-08-07 20:52:08", "count" : 1, "pub-type": "article", "journal": "Medical Image Analysis", "year": "2019", "url": "https://www.sciencedirect.com/science/article/pii/S136184151830865X", "author": [ "Hassan Al Hajj","Mathieu Lamard","Pierre-Henri Conze","Soumali Roychowdhury","Xiaowei Hu","Gabija Maršalkaitė","Odysseas Zisimopoulos","Muneer Ahmad Dedmari","Fenqiang Zhao","Jonas Prellberg","Manish Sahu","Adrian Galdran","Teresa Araújo","Duc My Vo","Chandan Panda","Navdeep Dahiya","Satoshi Kondo","Zhengbing Bian","Arash Vahdat","Jonas Bialopetravičius","Evangello Flouty","Chenhui Qiu","Sabrina Dill","Anirban Mukhopadhyay","Pedro Costa","Guilherme Aresta","Senthil Ramamurthy","Sang-Woong Lee","Aurélio Campilho","Stefan Zachow","Shunren Xia","Sailesh Conjeti","Danail Stoyanov","Jogundas Armaitis","Pheng-Ann Heng","William G. Macready","Béatrice Cochener","Gwenolé Quellec" ], "authors": [ {"first" : "Hassan", "last" : "Al Hajj"}, {"first" : "Mathieu", "last" : "Lamard"}, {"first" : "Pierre-Henri", "last" : "Conze"}, {"first" : "Soumali", "last" : "Roychowdhury"}, {"first" : "Xiaowei", "last" : "Hu"}, {"first" : "Gabija", "last" : "Maršalkaitė"}, {"first" : "Odysseas", "last" : "Zisimopoulos"}, {"first" : "Muneer Ahmad", "last" : "Dedmari"}, {"first" : "Fenqiang", "last" : "Zhao"}, {"first" : "Jonas", "last" : "Prellberg"}, {"first" : "Manish", "last" : "Sahu"}, {"first" : "Adrian", "last" : "Galdran"}, {"first" : "Teresa", "last" : "Araújo"}, {"first" : "Duc My", "last" : "Vo"}, {"first" : "Chandan", "last" : "Panda"}, {"first" : "Navdeep", "last" : "Dahiya"}, {"first" : "Satoshi", "last" : "Kondo"}, {"first" : "Zhengbing", "last" : "Bian"}, {"first" : "Arash", "last" : "Vahdat"}, {"first" : "Jonas", "last" : "Bialopetravičius"}, {"first" : "Evangello", "last" : "Flouty"}, {"first" : "Chenhui", "last" : "Qiu"}, {"first" : "Sabrina", "last" : "Dill"}, {"first" : "Anirban", "last" : "Mukhopadhyay"}, {"first" : "Pedro", "last" : "Costa"}, {"first" : "Guilherme", "last" : "Aresta"}, {"first" : "Senthil", "last" : "Ramamurthy"}, {"first" : "Sang-Woong", "last" : "Lee"}, {"first" : "Aurélio", "last" : "Campilho"}, {"first" : "Stefan", "last" : "Zachow"}, {"first" : "Shunren", "last" : "Xia"}, {"first" : "Sailesh", "last" : "Conjeti"}, {"first" : "Danail", "last" : "Stoyanov"}, {"first" : "Jogundas", "last" : "Armaitis"}, {"first" : "Pheng-Ann", "last" : "Heng"}, {"first" : "William G.", "last" : "Macready"}, {"first" : "Béatrice", "last" : "Cochener"}, {"first" : "Gwenolé", "last" : "Quellec"} ], "volume": "52","pages": "24-41","abstract": "Surgical tool detection is attracting increasing attention from the medical image analysis community. The goal generally is not to precisely locate tools in images, but rather to indicate which tools are being used by the surgeon at each instant. The main motivation for annotating tool usage is to design efficient solutions for surgical workflow analysis, with potential applications in report generation, surgical training and even real-time decision support. Most existing tool annotation algorithms focus on laparoscopic surgeries. However, with 19 million interventions per year, the most common surgical procedure in the world is cataract surgery. The CATARACTS challenge was organized in 2017 to evaluate tool annotation algorithms in the specific context of cataract surgery. It relies on more than nine hours of videos, from 50 cataract surgeries, in which the presence of 21 surgical tools was manually annotated by two experts. With 14 participating teams, this challenge can be considered a success. As might be expected, the submitted solutions are based on deep learning. This paper thoroughly evaluates these solutions: in particular, the quality of their annotations are compared to that of human interpretations. Next, lessons learnt from the differential analysis of these solutions are discussed. We expect that they will guide the design of efficient surgery monitoring tools in the near future.", "issn" : "1361-8415", "doi" : "https://doi.org/10.1016/j.media.2018.11.008", "bibtexKey": "ALHAJJ201924" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/28d432f872b56b4dfe35acfd2daa84745/michaelneumann", "tags" : [ "Automatic","CNN,","TIMIT","raw","recognition,","signal,","speech" ], "intraHash" : "8d432f872b56b4dfe35acfd2daa84745", "interHash" : "832d689a0226d54954717bfeae4f6c6d", "label" : "Analysis of cnn-based speech recognition system using raw speech as input", "user" : "michaelneumann", "description" : "", "date" : "2018-02-19 14:58:22", "changeDate" : "2018-02-19 13:58:22", "count" : 1, "pub-type": "inproceedings", "booktitle": "Proceedings of Interspeech", "year": "2015", "url": "", "author": [ "Dimitri Palaz","Ronan Collobert"," others" ], "authors": [ {"first" : "Dimitri", "last" : "Palaz"}, {"first" : "Ronan", "last" : "Collobert"}, {"first" : "", "last" : "others"} ], "date-added" : "2016-07-13 13:52:07 +0000", "date-modified" : "2017-02-21 12:22:17 +0000", "bdsk-file-1" : "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", "bibtexKey": "palaz2015analysis" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/249f467007f0f125661ed9b3261e4763d/thomasrichter", "tags" : [ "automatic","correction" ], "intraHash" : "49f467007f0f125661ed9b3261e4763d", "interHash" : "690695265035c7994d05f8a9311fd294", "label" : "Automatic Correction of Programming Exercises in ViPLab", "user" : "thomasrichter", "description" : "", "date" : "2016-03-10 09:18:49", "changeDate" : "2016-03-10 08:25:05", "count" : 3, "pub-type": "inproceedings", "booktitle": "Proc. of IEEE Symposium on Multimedia (ISM)","address":"Miami", "year": "2015", "url": "", "author": [ "Thomas Richter","Jan Vanvinkenroye" ], "authors": [ {"first" : "Thomas", "last" : "Richter"}, {"first" : "Jan", "last" : "Vanvinkenroye"} ], "bibtexKey": "richter2015automatic" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/245dcbc76b748c8e4c635d02ecdc4d5fb/isw-bibliothek", "tags" : [ "ISW","Kalman","automatic","equipment","estimation,","filter,","flow","foundry","pouring","rate","robot,","unscented" ], "intraHash" : "45dcbc76b748c8e4c635d02ecdc4d5fb", "interHash" : "1bdf6f5c937b919209a8de37c08f5e79", "label" : "Flow Rate Estimation Using Unscented Kalman Filterin Automatic Pouring Robot: Flow Rate Estimation Using Unscented Kalman Filterin Automatic Pouring Robot", "user" : "isw-bibliothek", "description" : "", "date" : "2016-03-03 09:53:12", "changeDate" : "2016-03-03 09:18:35", "count" : 1, "pub-type": "misc", "year": "2011", "url": "", "author": [ "Kazuhiko Terashima Oliver Sawodny Yoshiyuki Noda, Markus Birkhold","Alexander Verl" ], "authors": [ {"first" : "Kazuhiko Terashima Oliver Sawodny", "last" : "Yoshiyuki Noda, Markus Birkhold"}, {"first" : "Alexander", "last" : "Verl"} ], "pages": "--","abstract": "We describe here a method for estimating the pouring flow rate for tilting-ladle-type automatic pouring robotused in casting industries. To precisely pour molten metal into the mold, controlling the flow rate of liquid flowing outof the ladle is mandatory. However, it is difficult to directly measure the pouring flow rate by using a conventional flowmeter, because the flow meter is damaged by the high temperature molten metal. Therefore, in this study, we used a softsensing technique as part of the pouring flow rate estimation system. The extended Kalman filter was applied to the flowrate estimation of the automatic pouring robot in previous study. The previous approach can be applied only the ladlewith smooth shape, because of derivation of Jacobian matrix. However, some ladles with complicated shape which theJacobian matrix cannot be derived have been used in an actual casting plant. In this paper, an unscented Kalman filterwhich does not need the Jacobian matrix is applied into the flow rate estimation. The effectiveness of the proposed flowrate estimation method is demonstrated through simulations and experiments.", "__markedentry" : "[xtl:6]", "bibtexKey": "YoshiyukiNodaVerl2011" } ] }