Inhaltsverzeichnis
Auswahl der wissenschaftlichen Literatur zum Thema „Reverse image search“
Geben Sie eine Quelle nach APA, MLA, Chicago, Harvard und anderen Zitierweisen an
Machen Sie sich mit den Listen der aktuellen Artikel, Bücher, Dissertationen, Berichten und anderer wissenschaftlichen Quellen zum Thema "Reverse image search" bekannt.
Neben jedem Werk im Literaturverzeichnis ist die Option "Zur Bibliographie hinzufügen" verfügbar. Nutzen Sie sie, wird Ihre bibliographische Angabe des gewählten Werkes nach der nötigen Zitierweise (APA, MLA, Harvard, Chicago, Vancouver usw.) automatisch gestaltet.
Sie können auch den vollen Text der wissenschaftlichen Publikation im PDF-Format herunterladen und eine Online-Annotation der Arbeit lesen, wenn die relevanten Parameter in den Metadaten verfügbar sind.
Zeitschriftenartikel zum Thema "Reverse image search"
Al-Lohibi, Hanaa, Tahani Alkhamisi, Maha Assagran, Amal Aljohani und Asia Othaman Aljahdali. „Awjedni: A Reverse-Image-Search Application“. ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal 9, Nr. 3 (13.09.2020): 49–68. http://dx.doi.org/10.14201/adcaij2020934968.
Der volle Inhalt der QuelleKatasani, S. R., T. Rachepalli, N. Kamat und M. Jadhav. „Similar Fashion Finder using Reverse Image Search“. International Journal of Computer Sciences and Engineering 7, Nr. 5 (31.05.2019): 1190–95. http://dx.doi.org/10.26438/ijcse/v7i5.11901195.
Der volle Inhalt der QuelleSharifzadeh, Afsheen, und Gideon P. Smith. „Inaccuracy of Google reverse image search in complex dermatology cases“. Journal of the American Academy of Dermatology 84, Nr. 1 (Januar 2021): 202–3. http://dx.doi.org/10.1016/j.jaad.2020.04.107.
Der volle Inhalt der QuelleAraujo, Flavio H. D., Romuere R. V. Silva, Fatima N. S. Medeiros, Dilworth D. Parkinson, Alexander Hexemer, Claudia M. Carneiro und Daniela M. Ushizima. „Reverse image search for scientific data within and beyond the visible spectrum“. Expert Systems with Applications 109 (November 2018): 35–48. http://dx.doi.org/10.1016/j.eswa.2018.05.015.
Der volle Inhalt der QuelleLin, JianPu, WeiXing Wang, JianMin Yao, TaiLiang Guo, Enguo Chen und Qun Frank Yan. „Fast multi-view image rendering method based on reverse search for matching“. Optik 180 (Februar 2019): 953–61. http://dx.doi.org/10.1016/j.ijleo.2018.12.003.
Der volle Inhalt der QuelleZhang, Ke, und Zhao Gao. „The Technology of Fast 3D Reconstruction Based on Stereo Vision“. Key Engineering Materials 579-580 (September 2013): 654–58. http://dx.doi.org/10.4028/www.scientific.net/kem.579-580.654.
Der volle Inhalt der QuelleAmerini, Irene, Rudy Becarelli, Roberto Caldelli und Matteo Casini. „A Feature-Based Forensic Procedure for Splicing Forgeries Detection“. Mathematical Problems in Engineering 2015 (2015): 1–6. http://dx.doi.org/10.1155/2015/653164.
Der volle Inhalt der QuelleHokka, Jenni, und Matti Nelimarkka. „Affective economy of national-populist images: Investigating national and transnational online networks through visual big data“. New Media & Society 22, Nr. 5 (21.08.2019): 770–92. http://dx.doi.org/10.1177/1461444819868686.
Der volle Inhalt der QuelleReitelshöfer, Sebastian, Sebastian Meister und Jörg Franke. „Recognition and Description of Unknown Everyday Objects by Using an Image Based Meta-Search Engine for Service Robots“. Advanced Engineering Forum 19 (Oktober 2016): 132–38. http://dx.doi.org/10.4028/www.scientific.net/aef.19.132.
Der volle Inhalt der QuelleKunash, А. А. „Interpretation, topography and chronology of the greco-catholic medals of the XVII–XVIII centuries (according to archaeological research and analysis of private collections)“. Proceedings of the National Academy of Sciences of Belarus, Humanitarian Series 66, Nr. 1 (25.02.2021): 41–57. http://dx.doi.org/10.29235/2524-2369-2021-66-1-41-57.
Der volle Inhalt der QuelleDissertationen zum Thema "Reverse image search"
Jurečka, Tomáš. „Detekce a klasifikace létajících objektů“. Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2021. http://www.nusl.cz/ntk/nusl-442512.
Der volle Inhalt der QuelleCarvalho, José Ricardo de Abreu. „Pesquisa multimodal de imagens em dispositivos móveis“. Master's thesis, 2021. http://hdl.handle.net/10400.13/3984.
Der volle Inhalt der QuelleDespite the evolution in the field of reverse image search, with algorithms becoming more robust and effective, there still interest for improving search techniques, improving the user experience when searching for the images the user has in mind. The main goal of this work was to develop an application for mobile devices (smartphones) that would allow the user to find images through multimodal inputs. Thus, this dissertation, in addition to propose the search for images in different ways (keywords, drawing/sketching, and camera or device images), proposes that the user can create an image by himself through drawing, editing / changing an existing image, having feedback at the time of each change / interaction. Throughout the search experience, the user can use the images found (which it finds relevant) and improve the search through its edition, going against what it thinks to find. The implementation of this proposal was based on a Google Cloud Vision API responsible for obtaining the results, and the ATsketchkit framework that allowed the creation of drawings, for Apple's iOS system. Tests were carried out with a set of users with different levels of experience in image research and different drawing ability, allowing to assess preference in different input methods, satisfaction with the images retrieved, as well as the usability of the prototype.
Buchteile zum Thema "Reverse image search"
O’Neil, Fer. „Looking Forward to Reverse Image Search: Measuring the Effectiveness of Reverse Image Searches in Online Help“. In Advances in Intelligent Systems and Computing, 24–35. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-60477-0_3.
Der volle Inhalt der QuelleKansara, Dhvani, Aditya Shinde, Yashi Suba und Abhijit Joshi. „Optimizing Reverse Image Search by Generating and Assigning Suitable Captions to Images“. In Algorithms for Intelligent Systems, 621–31. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-3242-9_59.
Der volle Inhalt der QuelleWu, Dan, Chenyang Zhang, Abidan Ainiwaer und Siyu Lv. „Hybrid Research on Relevance Judgment and Eye Movement for Reverse Image Search“. In Diversity, Divergence, Dialogue, 211–28. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-71292-1_19.
Der volle Inhalt der QuelleSkelchy, Russell P. „Beyond Black and Gray“. In Vamping the Stage. University of Hawai'i Press, 2017. http://dx.doi.org/10.21313/hawaii/9780824869861.003.0013.
Der volle Inhalt der QuelleKonferenzberichte zum Thema "Reverse image search"
Singh, Paras Nath, und Tara P. Gowdar. „Reverse Image Search Improved by Deep Learning“. In 2021 IEEE Mysore Sub Section International Conference (MysuruCon). IEEE, 2021. http://dx.doi.org/10.1109/mysurucon52639.2021.9641572.
Der volle Inhalt der QuelleHorváth, András. „Object recognition based on Google's reverse image search and image similarity“. In Seventh International Conference on Graphic and Image Processing, herausgegeben von Yi Xie, Yulin Wang und Xudong Jiang. SPIE, 2015. http://dx.doi.org/10.1117/12.2228505.
Der volle Inhalt der QuelleBitirim, Yiltan, Selin Bitirim, Duygu Celik Ertugrul und Onsen Toygar. „An Evaluation of Reverse Image Search Performance of Google“. In 2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC). IEEE, 2020. http://dx.doi.org/10.1109/compsac48688.2020.00-65.
Der volle Inhalt der QuelleChutel, Pushpa M., und Apeksha Sakhare. „Evaluation of compact composite descriptor based reverse image search“. In 2014 International Conference on Communications and Signal Processing (ICCSP). IEEE, 2014. http://dx.doi.org/10.1109/iccsp.2014.6950085.
Der volle Inhalt der QuelleZhang, Jiajie, Bingsheng Zhang und Jiancheng Lin. „Recessive Social Networking: Preventing Privacy Leakage against Reverse Image Search“. In 2019 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW). IEEE, 2019. http://dx.doi.org/10.1109/eurospw.2019.00030.
Der volle Inhalt der QuelleMawoneke, Kudzai Felix, Xin Luo, Youqin Shi und Kenji Kita. „Reverse Image Search for the Fashion Industry Using Convolutional Neural Networks“. In 2020 IEEE 5th International Conference on Signal and Image Processing (ICSIP). IEEE, 2020. http://dx.doi.org/10.1109/icsip49896.2020.9339350.
Der volle Inhalt der QuelleDiyasa, I. Gede Susrama Mas, Alfath Daryl Alhajir, Amir Muhammad Hakim und Moh Fathur Rohman. „Reverse Image Search Analysis Based on Pre-Trained Convolutional Neural Network Model“. In 2020 6th Information Technology International Seminar (ITIS). IEEE, 2020. http://dx.doi.org/10.1109/itis50118.2020.9321037.
Der volle Inhalt der Quelle„Workshop: Information Search & Discovery, Using an Image as Query“. In InSITE 2019: Informing Science + IT Education Conferences: Jerusalem. Informing Science Institute, 2019. http://dx.doi.org/10.28945/4334.
Der volle Inhalt der QuelleSai, Y. Venkata, Salman und T. Sasikala. „An In-Depth Look at the Images for Finding Information using Deep learning and Reverse Image Search“. In 2021 5th International Conference on Trends in Electronics and Informatics (ICOEI). IEEE, 2021. http://dx.doi.org/10.1109/icoei51242.2021.9452817.
Der volle Inhalt der QuelleGandini, Martina, und Suela Ruffa. „A DOE Approach for Sensitivity Analysis of a Shape Partitioning Algorithm“. In ASME 2008 9th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2008. http://dx.doi.org/10.1115/esda2008-59175.
Der volle Inhalt der Quelle