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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 4 Hits 1 – 20 of 74 1 Face Biometric Spoof Detection Method Using a Remote Photoplethysmography Signal Seung-Hyun Kim; Su-Min Jeon; Eui Chul Lee In: Sensors; Volume 22; Issue 8; Pages: 3070 (2022) BASE Show details 2 ECG Recurrence Plot-Based Arrhythmia Classification Using Two-Dimensional Deep Residual CNN Features Bhekumuzi M. Mathunjwa; Yin-Tsong Lin; Chien-Hung Lin; Maysam F. Abbod; Muammar Sadrawi; Jiann-Shing Shieh In: Sensors; Volume 22; Issue 4; Pages: 1660 (2022) BASE Show details 3 Automatic Classification Framework of Tongue Feature Based on Convolutional Neural Networks Jiawei Li; Zhidong Zhang; Xiaolong Zhu; Yunlong Zhao; Yuhang Ma; Junbin Zang; Bo Li; Xiyuan Cao; Chenyang Xue In: Micromachines; Volume 13; Issue 4; Pages: 501 (2022) BASE Show details 4 Short Text Aspect-Based Sentiment Analysis Based on CNN + BiGRU Ziwen Gao; Zhiyi Li; Jiaying Luo; Xiaolin Li In: Applied Sciences; Volume 12; Issue 5; Pages: 2707 (2022) BASE Show details 5 BenSignNet: Bengali Sign Language Alphabet Recognition Using Concatenated Segmentation and Convolutional Neural Network Abu Saleh Musa Miah; Jungpil Shin; Md Al Mehedi Hasan; Md Abdur Rahim In: Applied Sciences; Volume 12; Issue 8; Pages: 3933 (2022) BASE Show details 6 Bangla Sign Language (BdSL) Alphabets and Numerals Classification Using a Deep Learning Model Kanchon Kanti Podder; Muhammad E. H. Chowdhury; Anas M. Tahir; Zaid Bin Mahbub; Amith Khandakar; Md Shafayet Hossain; Muhammad Abdul Kadir In: Sensors; Volume 22; Issue 2; Pages: 574 (2022) BASE Show details 7 TASE: Task-Aware Speech Enhancement for Wake-Up Word Detection in Voice Assistants Guillermo Cámbara; Fernando López; David Bonet; Pablo Gómez; Carlos Segura; Mireia Farrús; Jordi Luque In: Applied Sciences; Volume 12; Issue 4; Pages: 1974 (2022) BASE Show details 8 Rethinking the Methods and Algorithms for Inner Speech Decoding and Making Them Reproducible Foteini Simistira Liwicki; Vibha Gupta; Rajkumar Saini; Kanjar De; Marcus Liwicki In: NeuroSci; Volume 3; Issue 2; Pages: 226-244 (2022) BASE Show details 9 Recognition of Grammatical Class of Imagined Words from EEG Signals using Convolutional Neural Network Datta, S; Boulgouris, NV. - : Elsevier BV, 2021 BASE Show details 10 Deep Learning Methods for Human Behavior Recognition Lu, Jia. - : Auckland University of Technology, 2021 BASE Show details 11 Comparing Encoder-Decoder Architectures for Neural Machine Translation: A Challenge Set Approach ... Doan, Coraline. - : Université d'Ottawa / University of Ottawa, 2021 BASE Show details 12 Keyword Detection Based on RetinaNet and Transfer Learning for Personal Information Protection in Document Images Guo-Shiang Lin; Jia-Cheng Tu; Jen-Yung Lin In: Applied Sciences ; Volume 11 ; Issue 20 (2021) BASE Show details 13 Artificial Intelligence in Capsule Endoscopy: A Practical Guide to Its Past and Future Challenges Sang Hoon Kim; Yun Jeong Lim In: Diagnostics ; Volume 11 ; Issue 9 (2021) BASE Show details 14 A New Deep Learning-Based Methodology for Video Deepfake Detection Using XGBoost Aya Ismail; Marwa Elpeltagy; Mervat S. Zaki... In: Sensors ; Volume 21 ; Issue 16 (2021) BASE Show details 15 Deep Learning Based Air-Writing Recognition with the Choice of Proper Interpolation Technique Fuad Al Abir; Md. Al Siam; Abu Sayeed; Md. Al Mehedi Hasan; Jungpil Shin In: Sensors; Volume 21; Issue 24; Pages: 8407 (2021) BASE Show details 16 BengaliNet: A Low-Cost Novel Convolutional Neural Network for Bengali Handwritten Characters Recognition Abu Sayeed; Jungpil Shin; Md. Al Mehedi Hasan... In: Applied Sciences ; Volume 11 ; Issue 15 (2021) BASE Show details 17 Cardiovascular Disease Recognition Based on Heartbeat Segmentation and Selection Process Mehrez Boulares; Reem Alotaibi; Amal AlMansour... In: International Journal of Environmental Research and Public Health ; Volume 18 ; Issue 20 (2021) BASE Show details 18 Sentence Compression Using BERT and Graph Convolutional Networks Yo-Han Park; Gyong-Ho Lee; Yong-Seok Choi... In: Applied Sciences ; Volume 11 ; Issue 21 (2021) BASE Show details 19 Robust 3D Face Reconstruction Using One/Two Facial Images Ola Lium; Yong Bin Kwon; Antonios Danelakis... In: Journal of Imaging ; Volume 7 ; Issue 9 (2021) BASE Show details 20 Dynamic gesture classification of American Sign Language using deep learning Vaghasiya, Devina. - : Laurentian University of Sudbury, 2021 Abstract: American Sign Language (ASL) is a visual method of communication, utilized primarily by the hearing-impaired people. ASL is a sign language with 5 fundamental criterions: state of the hand, location (place of articulation), movement, palm orientation, and facial expressions. Since it is the most well-known gesture-based communication (sign language) of the world, it is essential to address dynamic sign gesture recognition for American Sign Language. To address the static sign language recognition in American Sign language a lot of studies have been done and researchers have claimed approximately 99% accuracy in static sign language recognition. There are very few studies currently available for dynamic gesture recognition in ASL. In this study, a subset of American Sign Language dataset was used, namely World-Level American Sign Language (WLASL) which has originally more than 2000 classes for gesturebased classification of American Sign Language from which we have chosen 100 classes. A combination of VGG16-LSTM, VGG19-LSTM, ResNet101-LSTM, Inception-LSTM and Inception3D based Convolutional Neural Networks (CNN) models were used for extracting spatial and temporal features respectively and applied them on the processed and extracted classes of videos from WLASL dataset. We found our model Inception3D outperformed the Visual Geometry Group-Long Short-Term Memory (VGG-LSTM) architectures, and ResNet101-LSTM models. These models have been compared based on model evaluation metric accuracy, thereby providing suitable insights on model selections. ; Master of Science (MSc) in Computational Sciences Keyword: American sign gestures; convolutional neural network; deep learning; long short-term memory (LSTM URL: https://zone.biblio.laurentian.ca/handle/10219/3843 BASE Hide details Page: 1 2 3 4

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