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Titlebook: Human-Computer Interaction. Recognition and Interaction Technologies; Thematic Area, HCI 2 Masaaki Kurosu Conference proceedings 2019 Sprin

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發(fā)表于 2025-3-28 16:13:12 | 只看該作者
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發(fā)表于 2025-3-29 04:35:06 | 只看該作者
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發(fā)表于 2025-3-29 08:44:11 | 只看該作者
,Die Krise der repr?sentativen Demokratie,ms efficiently. As 3D printers are increasingly adopted, designers are more likely to encounter difficulties in assembling 3D printers on their own, as the assembly process involves specialised skills and knowledge of fitting components in right positions. Conventional solutions use text and video m
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發(fā)表于 2025-3-29 14:57:18 | 只看該作者
https://doi.org/10.1007/978-3-663-12940-0 watchband under the screen. The board is optimized for the character input method named SliT (.-. .). Advantage of SliT is that the input speed of the novice is fast and the screen occupancy rate is low. Specifically, the speed is 28.7 [CPM (Characters Per Minute)] and the rate is 26.4%..In SliT, J
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發(fā)表于 2025-3-29 19:12:24 | 只看該作者
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發(fā)表于 2025-3-29 22:40:46 | 只看該作者
https://doi.org/10.1007/978-3-0348-6033-8h partner uses the same device setup (i.e., homogeneous device arrangements). In this work, we contribute an infrastructure that supports connection between a projector-camera media space and commodity mobile devices (i.e., tablets, smartphones). Deploying three device arrangements using this infras
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發(fā)表于 2025-3-30 01:02:46 | 只看該作者
https://doi.org/10.1007/978-3-658-11996-6e interaction and gesture recognition: when a user sketches a keyword by gesturing the first letters of its label, a menu with items related to the recognized letters is constructed dynamically and presented to the user for selection and auto-completion. The selection can be completed either gestura
50#
發(fā)表于 2025-3-30 06:13:46 | 只看該作者
https://doi.org/10.1007/978-3-663-12938-7on recognition based on deep convolutional neural networks (DCNNs) and extremely randomized trees. Specifically, we propose a method based on DCNN, which extracts informative features from the speech signal, and those features are then used by an extremely randomized trees classifier for emotion rec
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