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Καταστολή ηχητικού θορύβου μέσω τεχνικών μηχανικής μάθησης ...
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Effect of Lexical-Semantic Cues during Real-Time Sentence Processing in Aphasia
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In: Brain Sciences; Volume 12; Issue 3; Pages: 312 (2022)
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Mesh Clustering and Reordering Based on Normal Locality for Efficient Rendering
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In: Symmetry; Volume 14; Issue 3; Pages: 466 (2022)
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Real-Time Hand Gesture Recognition Using Fine-Tuned Convolutional Neural Network
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In: Sensors; Volume 22; Issue 3; Pages: 706 (2022)
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Articulation of geminate obstruents in the Ikema dialect of Miyako Ryukyuan: A real-time MRI analysis
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In: ISSN: 0025-1003 ; EISSN: 1475-3502 ; Journal of the International Phonetic Association ; https://hal.archives-ouvertes.fr/hal-03096154 ; Journal of the International Phonetic Association, Cambridge University Press (CUP), 2021, pp.1-25 ; https://www.cambridge.org/core/ (2021)
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Integration of Social Context vs. Linguistic Reference During Situated Language Processing ...
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«ПОЛЕВАЯ» ИДЕНТИФИКАЦИЯ ЧЕЛОВЕКА ... : «FIELDWORK» IDENTIFICATION OF A PERSON ...
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転置畳み込みニューラルネットワークを用いたrtMRIデータからの調音-音響変換
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In: https://ccd.ninjal.ac.jp/lrw2021.html (2021)
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口蓋3次元データの作成とWAVEでの発話計測実験への応用
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In: https://ccd.ninjal.ac.jp/lrw2021.html (2021)
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リアルタイムMRI動画データベースプロジェクトの概要と調音音声学への応用
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In: https://ccd.ninjal.ac.jp/lrw2021.html (2021)
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リアルタイムMRI調音動画データの閲覧および解析環境の開発
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In: https://ccd.ninjal.ac.jp/lrw2021.html (2021)
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リアルタイムMRI動画から抽出した声道の輪郭に基づく平均声道の基礎的検討
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In: https://ccd.ninjal.ac.jp/lrw2021.html (2021)
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A Survey on Sign Language Recognition ...
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Abstract:
The modern day applications are more user experience-oriented. Every application tends to gather information specific to each person’s operation and then provide customized features. The methods used to achieve such feats are a product of Machine Learning (ML) and Artificial Intelligence (AI) techniques. Using these techniques, real-time applications are reaching new heights in interacting with humans almost seamlessly. When living in such times, we can use these methods effectively to explore ways to overcome challenging problems. One such problem that we are taking upon is Sign Language Recognition (SLR). The project aims at bridging the communication gap with voice and hearing-impaired people, helping them to converse with the world more fluently. Using hand gestures as the primary input, we convert those into understandable language. ...
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Keyword:
Artificial Intelligence AI; Hand Gesture Recognition; Machine Learning ML; Real-Time Application; Sign Language Recognition SLR
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URL: https://zenodo.org/record/4902967 https://dx.doi.org/10.5281/zenodo.4902967
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Selection of Key Frames for 3D Reconstruction in Real Time
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In: Algorithms ; Volume 14 ; Issue 11 (2021)
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Soundpainting Sign Language: Possibilities and Connections with Tactileology
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In: Philosophies ; Volume 6 ; Issue 3 (2021)
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Integration of Social Context vs. Linguistic Reference During Situated Language Processing
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Referential vs. Non-referential World-Language Relations: How Do They Modulate Language Comprehension in 4 to 5-Year-Olds, Younger, and Older Adults?
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Calibrate to innovate: Community age vectors and the real time incrementation of language change
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Aging and Referential Communication: Insights from Interactions with Artificial Agents
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