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The impact of the Lombard effect on audio and visual speech recognition systems
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In: ISSN: 0167-6393 ; EISSN: 1872-7182 ; Speech Communication ; https://hal.archives-ouvertes.fr/hal-01779704 ; Speech Communication, Elsevier : North-Holland, 2018, 100, pp.58-68. ⟨10.1016/j.specom.2018.04.006⟩ (2018)
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Cultural Differences in Pattern Matching: Multisensory Recognition of Socio-affective Prosody
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In: Interspeech 2018 ; https://hal.archives-ouvertes.fr/hal-01913705 ; Interspeech 2018, Sep 2018, Hyderabad, India. ⟨10.21437/interspeech.2018-1795⟩ (2018)
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ASR performance prediction on unseen broadcast programs using convolutional neurol networks
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In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) ; https://hal.archives-ouvertes.fr/hal-01709779 ; IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Apr 2018, Calgary, Alberta, Canada (2018)
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Impact of the face registration techniques on facial expressions recognition
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In: ISSN: 0923-5965 ; EISSN: 1879-2677 ; Signal Processing: Image Communication ; https://hal.archives-ouvertes.fr/hal-01644769 ; Signal Processing: Image Communication, Elsevier, 2018, 61, pp.44-53. ⟨10.1016/j.image.2017.11.002⟩ (2018)
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Inferring Availability for Communication in Smart Homes Using Context
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In: PerCom 2018 - IEEE International Conference on Pervasive Computing and Communications ; https://hal.archives-ouvertes.fr/hal-01762137 ; PerCom 2018 - IEEE International Conference on Pervasive Computing and Communications, Mar 2018, Athènes, Greece. pp.1-6 (2018)
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DEEP-SEE FACE: a mobile face recognition system dedicated to visually impaired people
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In: ISSN: 2169-3536 ; EISSN: 2169-3536 ; IEEE Access ; https://hal.archives-ouvertes.fr/hal-01993883 ; IEEE Access, IEEE, 2018, 6, pp.51975 - 51985. ⟨10.1109/ACCESS.2018.2870334⟩ (2018)
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Protocol for Systematic Literature Review of Face Recognition in Uncontrolled Environment
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In: ISSN: 2032-9407 ; EAI Endorsed Transactions on Scalable Information Systems ; https://hal.archives-ouvertes.fr/hal-02075677 ; EAI Endorsed Transactions on Scalable Information Systems , European Alliance for Innovation, 2018, 5 (16), pp.e11. ⟨10.4108/eai.13-4-2018.154477⟩ (2018)
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Handwritten Sindhi Character Recognition Using Neural Networks
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In: ISSN: 0254-7821 ; Mehran University Research Journal of Engineering and Technology ; https://hal.archives-ouvertes.fr/hal-01676725 ; Mehran University Research Journal of Engineering and Technology, Mehran University of Engineering and Technology, Jamshoro, Pakistan, 2018, 37 (1), pp.191-196 ; http://publications.muet.edu.pk/index.php/muetrj/article/view/122/63 (2018)
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A Multilinear Tongue Model Derived from Speech Related MRI Data of the Human Vocal Tract
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In: ISSN: 0885-2308 ; EISSN: 1095-8363 ; Computer Speech and Language ; https://hal.archives-ouvertes.fr/hal-01418460 ; Computer Speech and Language, Elsevier, 2018, 51, pp.68-92. ⟨10.1016/j.csl.2018.02.001⟩ (2018)
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How many voices did you hear? Natural variability disrupts identity perception from unfamiliar voices.
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Applied Screening Tests for the Detection of Superior Face Recognition
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The Limits of Super Recognition: An Other-Ethnicity Effect in Individuals with Extraordinary Face Recognition Skills
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Recognition and discrimination: Is there a role for context in face learning?
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Linguistically-driven framework for computationally efficient and scalable sign recognition
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Scalable ASL sign recognition using model-based machine learning and linguistically annotated corpora
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A study of facial expression recognition technologies on deaf adults and their children
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When does less yield more? The impact of severity upon implicit recognition in pure alexia
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Real-time Face Detection and Recognition Based on Deep Learning
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Wang, Hui. - : Auckland University of Technology, 2018
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Abstract:
Face recognition is one of the most important applications in video surveillance and computer vision. However, the conventional algorithms of face recognition are susceptible to multiple conditions, such as lighting, occlusion, viewing angle or camera rotation. Therefore, face recognition based on deep learning can greatly improve the recognition speed and compatible external interference. In this thesis, we use convolutional neural networks (ConvNets) for face recognition, the neural networks have the merits of end-to-end, sparse connection and weight sharing. The purpose of this thesis project is to identify the name of different people based on location of the detected box of a face. Then, we can obtain recognition results with different confidence under various distances. This thesis presents different methods with comparisons, namely, comparing the training results and the test results of different parameters under the same model, training results of the same test video under different models. We find that the recognition accuracy of this model is mainly affected by face proportion and the number of samples. If we get larger proportion of a face on screen, then we have higher recognition accuracy; if we obtain much greater number of samples, we can get higher recognition accuracy. In this work, we first collect sufficient samples as our dataset and use the suitable model embedded in the platform Google TensorFlow to complete the training and test. We collected five different faces and obtained 500 images on each face as training set, each of which can be cropped and rotated by using 50 different angles of the picture having a human face, of which 40 for training, 10 for verification. The use of neural networks for face recognition improves the speed of recognition. The contributions of this thesis are: (1) The use of elliptical markers can identify a human face including rotation and position. (2) The confidence of human face recognition is mainly affected by the proportion of face occupied on the screen.
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Keyword:
CNNs; Data augmentation; Face recognition; Inception v2; SSD
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URL: http://hdl.handle.net/10292/11866
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Pronounceability and Visual Recognition Processing: The Role of Phonology in Word Identification Under the Mixed-Case Situation
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In: Senior Projects Spring 2018 (2018)
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Introducing the XXX Bangla Handwriting Dataset and an Efficient Offline Recognizer of Isolated Bangla Characters
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In: Electrical and Computer Engineering Faculty Publications and Presentations (2018)
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