Relevant bibliographies by topics / Dlib

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Dlib'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 April 2022

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Journal articles on the topic "Dlib"

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Solis-Toapanta, Elisa, and Celina Gómez. "Growth and Photosynthetic Capacity of Basil Grown for Indoor Gardening under Constant or Increasing Daily Light Integrals." HortTechnology 29, no. 6 (December 2019): 880–88. http://dx.doi.org/10.21273/horttech04442-19.

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In the quest to identify minimum daily light integrals (DLIs) that can sustain indoor gardening, we evaluated DLIs less than the recommended ranges for commercial production of basil (Ocimum basilicum). Experiments were conducted for 8 weeks to evaluate the effect of providing a constant vs. an increasing DLI over time (DLIInc) on growth and photosynthetic capacity of green (‘Genovese Compact’) and purple (‘Red Rubin’) basil grown hydroponically under a constant ambient temperature of 21 °C. Plants were grown under a 14 h·d–1 photoperiod and were subjected to the following DLI treatments: 4 (DLI4), 6 (DLI6), 8 (DLI8), or 10 (DLI10) mol·m–2·d‒1 (80, 119, 159, and 197 µmol·m‒2·s‒1, respectively); DLIInc was used as a fifth treatment and was achieved by transitioning hydroponic systems systematically to treatments with greater DLIs every 2 weeks. In general, regardless of cultivar, leaf area, leaf number, and overall growth [shoot fresh weight (SFW) and shoot dry weight (SDW)] were similar for plants grown under DLIInc to DLI4 and DLI6 during weeks 2, 4, and 6. However, plants grown under DLIInc produced the same leaf area as those grown under DLI10 at week 8. Nonetheless, across weeks, growth was significantly less under DLIInc compared with DLI10, but similar to that produced by DLI8 at week 8. Photosynthetic responses were significant only at week 8, for which leaves of plants grown under DLI8, DLI10, and DLIInc had 15% to 25% greater maximum gross carbon dioxide (CO2) assimilation (Amax) than plants grown under DLI4. The light saturation point of photosynthesis was unaffected by DLI, but showed a general increasing trend with greater DLIs. Overall, our results suggest that providing a constantly high DLI results in greater growth and yield than increasing the DLI over time. In addition, we found that changes in Amax and the light saturation point are not good indicators of the capacity of whole plants to make use of the available light for photosynthesis and growth. Instead, morphological and developmental traits regulated by DLI during the initial stages of production are most likely responsible for the growth responses measured in our study.
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Sejati, RR Puji Hajar, and Rodhiyah Mardhiyyah. "Deteksi Wajah Berbasis Facial Landmark Menggunakan OpenCV Dan Dlib." Jurnal Teknologi Informasi 5, no. 2 (December 31, 2021): 144–48. http://dx.doi.org/10.36294/jurti.v5i2.2220.

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Computer science and information technology have advanced in a variety of sectors that were previously unachievable due to constraints such as hardware. Computer vision can be used to recognize an object using computer science. Objects can be recognized by taking or recording photos or videos and then processing them using specific tools and methodologies. The goal of the facial landmark-based face detection research using OpenCV and Dlib is to perform face detection in people so that it can be used for a variety of purposes in the future. The strategy employed in this study was the usage of facial landmarks using OpenCV and Dlib to improve face detection accuracy. Face detection has been effectively carried out based on facial landmark points, according to the findings of testing the entire system. Face landmark-based face detection is more accurate using the OpenCV Dlib, which can be seen during processing in the OpenCV Dlib, which can precision photos based on facial movements.
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Lia Farokhah. "Perbandingan Metode Deteksi Wajah Menggunakan OpenCV Haar Cascade, OpenCV Single Shot Multibox Detector (SSD) dan DLib CNN." Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) 5, no. 3 (June 29, 2021): 609–14. http://dx.doi.org/10.29207/resti.v5i3.3125.

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Comparison of methods in face detection is needed to provide recommendation of best method. This study compared three methods in face detection, namely OpenCV haar cascade, OpenCV Single Shot Multibox Detector (SSD) and Dlib CNN. Face detection is focused on five challenging conditions, namely face detection in head position obstacles, wearing face masks, lighting, background images that have a lot of noise, differences in expression. Data testing is taken randomly on google with reference to one image consisting of more than one detected face with wild condition. The results of the comparative analysis in wild condition show that the OpenCV haar cascade has more weaknesses with a performance percentage of 20% compared OpenCV SSD and Dlib CNN method. Performance results of SSD and Dlib CNN have the same performance in the five conditions tested, which is about 80%.
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Suwarno, Suwarno, and Kevin Kevin. "Analysis of Face Recognition Algorithm: Dlib and OpenCV." JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING 4, no. 1 (July 20, 2020): 173–84. http://dx.doi.org/10.31289/jite.v4i1.3865.

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In face recognition there are two commonly used open-source libraries namely Dlib and OpenCV. Analysis of facial recognition algorithms is needed as reference for software developers who want to implement facial recognition features into an application program. From Dlib algorithm to be analyzed is CNN and HoG, from OpenCV algorithm is DNN and HAAR Cascades. These four algorithms are analyzed in terms of speed and accuracy. The same image dataset will be used to test, along with some actual images to get a more general analysis of how algorithm will appear in real life scenarios. The programming language used for face recognition algorithms is Python. The image dataset will come from LFW (Labeled Faces in the Wild), and AT&T, both of which are available and ready to be downloaded from the internet. Pictures of people around the UIB (Batam International University) is used for actual images dataset. HoG algorithm is fastest in speed test (0.011 seconds / image), but the accuracy rate is lower (FRR = 27.27%, FAR = 0%). DNN algorithm is the highest in level of accuracy (FRR = 11.69%, FAR = 2.6%) but the lowest speed (0.119 seconds / picture). There is no best algorithm, each algorithm has advantages and disadvantages.Keywords: Python, Face Recognition, Analysis, Speed, Accuracy.
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Abdul Haris, Muhamad Amin Husni, and Sin Liang Lim. "Neural Network Facial Authentication for Public Electric Vehicle Charging Station." Journal of Engineering Technology and Applied Physics 3, no. 1 (June 15, 2021): 17–21. http://dx.doi.org/10.33093/jetap.2021.3.1.4.

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This study is to investigate and compare the facial recognition accuracy performance of Dlib ResNet against a K-Nearest Neighbour (KNN) classifier. Particularly when used against a dataset from an Asian ethnicity as Dlib ResNet was reported to have an accuracy deficiency when it comes to Asian faces. The comparisons are both implemented on the facial vectors extracted using the Histogram of Oriented Gradients (HOG) method and use the same dataset for a fair comparison. Authentication of a user by facial recognition in an electric vehicle (EV) charging station demonstrates a practical use case for such an authentication system.
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Yang, Jianxing, Jianhua Adu, Hongguang Chen, Jie Zhang, and Jianfeng Tang. "A Facial Expression Recongnition Method Based on Dlib, RI-LBP and ResNet." Journal of Physics: Conference Series 1634 (September 2020): 012080. http://dx.doi.org/10.1088/1742-6596/1634/1/012080.

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Chen, Long, Guojiang Xin, Yuling Liu, and Junwei Huang. "Driver Fatigue Detection Based on Facial Key Points and LSTM." Security and Communication Networks 2021 (June 12, 2021): 1–9. http://dx.doi.org/10.1155/2021/5383573.

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In recent years, fatigue driving has been a serious threat to the traffic safety, which makes the research of fatigue detection a hotspot field. Research on fatigue recognition has a great significance to improve the traffic safety. However, the existing fatigue detection methods still have room for improvement in detection accuracy and efficiency. In order to detect whether the driver has fatigue driving, this paper proposes a fatigue state recognition algorithm. The method first uses MTCNN (multitask convolutional neural network) to detect human face, and then DLIB (an open-source software library) is used to locate facial key points to extract the fatigue feature vector of each frame. The fatigue feature vectors of multiple frames are spliced into a temporal feature sequence and sent to the LSTM (long short-term memory) network to obtain a final fatigue feature value. Experiments show that compared with other methods, the fatigue state recognition algorithm proposed in this paper has achieved better results in accuracy. The average accuracy of the proposed method in detecting key points of the face is as high as 93%, and the running time is less than half of the ordinary DLIB method.
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Galinium, Maulahikmah, Timothy Aditya Sutantyo, and Eka Budiarto. "Implementation For Augmentative And Alternative Communication (AAC) Tools For Rett Syndrome Individual In Activities Of Daily Living (ADL)." Prosiding Konferensi Nasional Pengabdian Kepada Masyarakat dan Corporate Social Responsibility (PKM-CSR) 2 (December 15, 2019): 368–76. http://dx.doi.org/10.37695/pkmcsr.v2i0.708.

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Rett Syndrome occurs between one in 10000 to 15000 girls in Indonesia. In Hasan Sadikin Hospital, Bandung, Indonesia, there is a girl suffering from Rett Syndrome. Doctors in Hasan Sadikin Hospital find a lot of difficulties in communicating with the patient, since Rett Syndrome patients has little-to-no speech capabilities, and their hands often move involuntarily, especially with regards to Activities of Daily Living (ADL). Hence, a method to communicate with Rett Syndrome patient is being proposed using Augmentative and Alternative Communication (AAC) to support communication between the caregiver and the patient. Two of those methods are using gaze-tracking and head-pose. The methods tested consists of head-pose algorithm, gaze-tracking with Dlib, gaze-tracking with Haar Cascades, and EyeTribe. Each method is tested first with normal people before being tested with the patient. EyeTribe, head-pose, and gaze-tracking algorithm using Dlib achieve good results, with the best results being at 50cm distance and with high light intensity, however the Rett Syndrome patient achieves poor results when using the application, although head-pose achieves the best results in terms of determining needed ADL at around 45% accuracy. Hence, the Rett Syndrome patient needs training to use the application properly.
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Ye, Kai, Jianmin Dong, and Lijun Zhang. "Digital Analysis of Movements on Characters Based on OpenPose and Dlib from Video." Journal of Physics: Conference Series 2218, no. 1 (March 1, 2022): 012021. http://dx.doi.org/10.1088/1742-6596/2218/1/012021.

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Abstract In order to avoid the disadvantages of complex operation and expensive equipment for the extraction method of motion capture systems and other equipment , a method which can extract key points of characters movements was proposed based on video of Tibetan drama with OpenPose and Dlib. And, the movement trajectory and movement fluctuation amplitude which were obtained by digital analysis from characters’ movement were used as indicators to provide a quantitative plan for movement essentials of Tibetan drama’s performing arts. The digital analysis was implemented by tracking key points’ two-dimensional coordinate data with the form of line chart and reflecting movement fluctuation amplitude with absolute difference of the same key point’s two-dimensional coordinate data belonged to two frame of video. Experiments showed that this method was suitable for video and was correct and effective in the image coordinate system, which provided a reliable foundation for the digital analysis.
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Zhegallo, A. V. "Tracking moving objects on video in psychological studies." Experimental Psychology (Russia) 12, no. 4 (2019): 5–11. http://dx.doi.org/10.17759/exppsy.2019120401.

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The article discusses the possibilities of using OpenCV and dlib libraries to track the position of specified objects on the video image and to track a set of landmark points of the human face. It is shown that these problems can be effectively solved with the help of compact programs in Python. The Python language is recommended to the attention of research psychologists as an instrument for analyzing video images and constructing complex experiments.
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Dissertations / Theses on the topic "Dlib"

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Hermkens, Anna-Karina. "The way of the objects analogical inference and the allocation of meaning and order in Lapita, Dongson and Lake Sentani material culture /." Website, 1997. http://www.papuaweb.org/dlib/s123/hermkens/_ma.html.

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Giay, Benny. "Zakheus Pakage and his communities indigenous religious discourse, socio-political resistance, and ethnohistory of the Me of Irian Jaya /." [Indonesia] : UNIPA-ANU-UNCEN PapuaWeb Project, 2002. http://www.papuaweb.org/dlib/s123/giay/%5Fphd.html.

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O'Hare, Martin. "The Indonesian military in Irian Jaya." [Canberra : Strategic and Defence Studies Centre, Research School of Pacific Studies, Australian National Univerity], 1991. http://www.papuaweb.org/dlib/s123/ohare2/%5Fma.html.

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Kirksey, S. Eben. "Saya makan sembarang (I eat anything) the changing world of the Oge Bage Mee /." [Sarasota, Fla.] : Division of Social Sciences, Division of Natural Sciences, New College of the University of South Florida, 2002. http://www.papuaweb.org/dlib/s123/kirksey1/%5Frk.html.

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Kjar, Renée Giay Benny. "The invisible aristocrat Benny Giay in Papuan history /." [Sydney, Australia] : Australiann National University, Discipline of Asian Studies, 2002. http://www.papuaweb.org/dlib/s123/kjar/%5Fba.pdf.

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Thesis (B.A.)--Discipline of Asian Studies, Australian National University, 2002.
Title from thesis home page (viewed Dec. 6, 2004). Title from start screen (viewed Aug. 19, 2004). "December 2002."
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Godschalk, Jan Anthonie. "Sela Valley : an ethnography of a Mek society in the Eastern Highlands, Irian Jaya, Indonesia /." Amsterdam : Vrije Universiteit, 1993. http://www.papuaweb.org/dlib/s123/godschalk/00.pdf.

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Thesis (doctoral)--Vrije Universiteit te Amsterdam, 1993.
Basic text in English; partial t.p. in Dutch; summaries in English, Dutch, and Una. "Stellingen" laid in. Includes bibliographical references (p. [157]-164) and index. Also issued online.
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Dasgupta, Sankarshan. "3D Face Reconstruction From Front And Profile Image." University of Dayton / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1626689472561706.

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Malý, Ondřej. "Detekce zahalených tváří v obraze." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2020. http://www.nusl.cz/ntk/nusl-413097.

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The aim of this work is to study and test current methods for face detection on veiled faces and evaluate the results. In the first chapter, five selected methods are theoretically analyzed and in the second chapter the individual methods are evaluated, both for the Wider Face file and for the actual set of photos with veiled faces. Subsequently, the Dlib CNN method is improved for better detection of veiled faces and reprogrammed to detect the degree of veil from the tested image
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Skoták, Jiří. "Hra pro mobilní telefon s využitím rozpoznání rysů tváře." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2019. http://www.nusl.cz/ntk/nusl-403200.

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This master's thesis focuses on smartphone game for iOS, which uses recognition of face features and other information, which can be obtained from a smartphone's camera and sensors. This work describes a few approaches for real-time face detection and then introduces and compares possibilities for such task on iOS. Moreover, the thesis contains a draft of the final game and its levels. The game showcases various technologies in its levels such as object detection, processing an image color and others. Finally, the thesis introduces the final form of the game that is released and available on the App Store.
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Hřebíček, Pavel. "Mobilní aplikace pro rozpoznání leukokorie ze snímku lidského obličeje." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2019. http://www.nusl.cz/ntk/nusl-403140.

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The goal of this thesis is to design and implement a multiplatform multilingual mobile application for detecting leukocoria in an image of human face for iOS and Android platforms. Leukocoria is a whitish light of the pupil, which can be seen on the photo when the flash is used. Early detection of this symptom can save human eyesight. The application itself allows to analyze a user's photo and detect the presence of leukocoria. The goal of the application is to analyze eyes of the human, from which the mobile application name - Eye Check is derived. React Native framework was used to create a multiplatform mobile application. The Dlib library was chosen for human face and eye detection, the OpenCV library for working with the photo. The convolutional neural network was used to classify the eyes for the possible presence of leukocoria. Client-Server communication is solved using the REST architecture. The result is a mobile application that detects leukocoria and allerts the user to visit his doctor if leukocoria is detected.
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Books on the topic "Dlib"

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Dlin, Barney M. [Dlin] =: Dlin family history. [S.l: s.n., 1986.

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Ortyns'kyi, Ivan. Tri kol'ory: Dlia rozdumu s'ohodni dlia tebe. L'viv: SDB, 1997.

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Vilʹmont, Ekaterina. Maskirovka dlia zlodeĭki. Moskva: "ĖKSMO", 2003.

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Bibish. Tok-shou dlia prostodushnoi. Sankt-Peterburg: Azbuka-klassika, 2005.

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Ovsienko, Yuliya Georgievna. Russkii iazyk dlia nachinaiushchikh. 2nd ed. Moskva: Russkii Iazyk, 1992.

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Kremer, Naum Shevelevich. Ekonometrika: Uchebnik dlia vuzov. Moskva: IUNITI-DANA, 2002.

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Slavkin, Vladimir Viacheslavovich. Russkii iazyk dlia vsekh: Uchebnoe posobie dlia izuchaiushchikh russkii iazyk kak vtoroi. Moskva: Drofa, 1995.

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Mazurov, V. I. Klinicheskaia revmatologiia: Rukovodstvo dlia vrachei. Sankt-Peterburg: Foliant, 2005.

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Smetnik, V. P. Neoperativnaia ginekologiia: Rukovodstvo dlia vrachei. 2nd ed. Sankt-Peterburg: Sotis, 1995.

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Kheivud, E. Politologiia: Uchebnik dlia studentov vuzov. Moskva: IUNITI, 2005.

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Book chapters on the topic "Dlib"

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Xu, Min, Daijiang Chen, and Guangheng Zhou. "Real-Time Face Recognition Based on Dlib." In Lecture Notes in Electrical Engineering, 1451–59. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5959-4_177.

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Rohra, Anjum, and Ramesh K. Kulkarni. "Face Swapping Using Modified Dlib Image Morphology." In Innovative Data Communication Technologies and Application, 213–21. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-38040-3_25.

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Babu, Athira, Shruti Nair, and K. Sreekumar. "Driver’s Drowsiness Detection System Using Dlib HOG." In Smart Innovation, Systems and Technologies, 219–29. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-3675-2_16.

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Feng, Yuanyong, Zhidong Xie, and Fufang Li. "Intelligent Virtual Lipstick Trial Makeup Based on OpenCV and Dlib." In Advances in Intelligent Systems and Computing, 121–27. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-8462-6_14.

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Kavitha, R., P. Subha, R. Srinivasan, and M. Kavitha. "Implementing OpenCV and Dlib Open-Source Library for Detection of Driver’s Fatigue." In Innovative Data Communication Technologies and Application, 353–67. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-7167-8_26.

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Feyer, Stefan, Sophie Siebert, Bela Gipp, Akiko Aizawa, and Joeran Beel. "Integration of the Scientific Recommender System Mr. DLib into the Reference Manager JabRef." In Lecture Notes in Computer Science, 770–74. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56608-5_80.

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Hien, Tran Thi, Qiaokang Liang, and Nguyen Thi Dieu Linh. "Design Driver Sleep Warning System Through Image Recognition and Processing in Python, Dlib, and OpenCV." In Intelligent Systems and Networks, 386–93. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-2094-2_47.

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Simola, Nicola, Micaela Morelli, Tooru Mizuno, Suzanne H. Mitchell, Harriet de Wit, H. Valerie Curran, Celia J. A. Morgan, et al. "DLB." In Encyclopedia of Psychopharmacology, 416. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-540-68706-1_4206.

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Metze, Dieter, Tam Nguyen, Birgit Haack, Alexander K. C. Leung, Noriko Miyake, Naomichi Matsumoto, A. J. Larner, et al. "DLB." In Encyclopedia of Molecular Mechanisms of Disease, 540. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-29676-8_8340.

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Hashimoto, Shu, Mari Hikichi, Mai Takahashi, and Yasuhiro Gon. "Diagnostic Approach for DLI: How is DLI Diagnosed?" In Respiratory Disease Series: Diagnostic Tools and Disease Managements, 37–44. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-4466-3_4.

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Conference papers on the topic "Dlib"

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Beel, Joeran, Bela Gipp, Stefan Langer, Marcel Genzmehr, Erik Wilde, Andreas Nürnberger, and Jim Pitman. "Introducing Mr. DLib,." In Proceeding of the 11th annual international ACM/IEEE joint conference. New York, New York, USA: ACM Press, 2011. http://dx.doi.org/10.1145/1998076.1998187.

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Ren, Xiujuan, Junhang Ding, Jinna Sun, and Qingmei Sui. "Face modeling process based on Dlib." In 2017 Chinese Automation Congress (CAC). IEEE, 2017. http://dx.doi.org/10.1109/cac.2017.8243093.

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Zhang, Dujuan, Jie Li, and Zhenfang Shan. "Implementation of Dlib Deep Learning Face Recognition Technology." In 2020 International Conference on Robots & Intelligent System (ICRIS). IEEE, 2020. http://dx.doi.org/10.1109/icris52159.2020.00030.

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Ali, Nawazish, Imran Hasan, Tansel Ozyer, and Reda Alhajj. "Driver Drowsiness Detection by Employing CNN and Dlib." In 2021 22nd International Arab Conference on Information Technology (ACIT). IEEE, 2021. http://dx.doi.org/10.1109/acit53391.2021.9677197.

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Sharma, S., Karthikeyan Shanmugasundaram, and Sathees Kumar Ramasamy. "FAREC — CNN based efficient face recognition technique using Dlib." In 2016 International Conference on Advanced Communication Control and Computing Technologies (ICACCCT). IEEE, 2016. http://dx.doi.org/10.1109/icaccct.2016.7831628.

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Mohanty, Shruti, Shruti V. Hegde, Supriya Prasad, and J. Manikandan. "Design of Real-time Drowsiness Detection System using Dlib." In 2019 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE). IEEE, 2019. http://dx.doi.org/10.1109/wiecon-ece48653.2019.9019910.

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Beel, Joeran, Akiko Aizawa, Corinna Breitinger, and Bela Gipp. "Mr. DLib: Recommendations-as-a-Service (RaaS) for Academia." In 2017 ACM/IEEE Joint Conference on Digital Libraries (JCDL). IEEE, 2017. http://dx.doi.org/10.1109/jcdl.2017.7991606.

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Sanchez, Earle Kit M., Noel B. Linsangan, and Randy E. Angelia. "Three Triangle Method for Face Recognition using Dlib and OpenCV." In 2020 IEEE 12th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM). IEEE, 2020. http://dx.doi.org/10.1109/hnicem51456.2020.9400134.

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Xia, Han, and Chunfang Li. "Face Recognition and Application of Film and Television Actors Based on Dlib." In 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI). IEEE, 2019. http://dx.doi.org/10.1109/cisp-bmei48845.2019.8965869.

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Gamage, G., I. Sudasingha, I. Perera, and D. Meedeniya. "Reinstating Dlib Correlation Human Trackers Under Occlusions in Human Detection based Tracking." In 2018 18th International Conference on Advances in ICT for Emerging Regions (ICTer). IEEE, 2018. http://dx.doi.org/10.1109/icter.2018.8615551.

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Reports on the topic "Dlib"

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Pan, Zhengxiang, and Jeff Heflin. DLDB: Extending Relational Databases to Support Semantic Web Queries. Fort Belvoir, VA: Defense Technical Information Center, January 2004. http://dx.doi.org/10.21236/ada451847.

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SWA CONSULTING INC RALEIGH NC. Evaluating DLAB as a Predictor of Foreign Language Learning. Fort Belvoir, VA: Defense Technical Information Center, May 2012. http://dx.doi.org/10.21236/ada585073.

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Bienkowski, Sarah C., Sean Gasperson, Reanna Poncheri Harman, Amber Harris, Nathaniel Phillips, Eric A. Surface, and Stephen J. Ward. Special Operations Forces Language and Culture Needs Assessment Project: Defense Language Aptitude Battery (DLAB): Perspectives from the Field. Fort Belvoir, VA: Defense Technical Information Center, September 2010. http://dx.doi.org/10.21236/ada634214.

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