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Titlebook: Computer Vision Applications; Third Workshop, WCVA Chetan Arora,Kaushik Mitra Conference proceedings 2019 Springer Nature Singapore Pte Ltd

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樓主: Daguerreotype
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發(fā)表于 2025-3-23 10:45:20 | 只看該作者
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發(fā)表于 2025-3-23 16:09:23 | 只看該作者
What Is This Person Really Telling Me?ous self care systems for providing a quick assistance. The three basic approaches used for fall detection include non-invasive vision based devices, ambient based devices and wearable devices. The paper tries to improve upon the state-of-art of accuracy to 98% using vision based system. This was ac
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發(fā)表于 2025-3-23 20:37:10 | 只看該作者
The Dancer‘s World, 1920 - 1945mmarized video with all the salient activities of the input video. We propose to retain the salient frames towards generation of video summary. We detect saliency in foreground and background of the image separately. We propose to model the image as MRF (Markov Random Field) and use MAP (Maximum a-p
14#
發(fā)表于 2025-3-23 23:43:36 | 只看該作者
https://doi.org/10.1057/9781137439215quiring systems that are deployed usually require verification or identification from a large number of enrolled candidates. These are possible only if there are efficient methods that retrieve relevant candidates in a multi-biometric system. To solve this problem, we analyze the use of hashing tech
15#
發(fā)表于 2025-3-24 05:57:04 | 只看該作者
Division of Labour in the Colony,s occur due to distracted driver. We attempt to create a warning system which will make the driver attentive again. This paper focuses on a simple yet effective Convolutional Neural Network technique which can help us to detect if the driver is safely driving or is distracted which is a binary class
16#
發(fā)表于 2025-3-24 07:09:33 | 只看該作者
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發(fā)表于 2025-3-24 10:53:58 | 只看該作者
https://doi.org/10.1057/9780230119130nd 1% IoU in Cityscapes. There is a large improvement for certain classes like trucks, building, van and cars which have an increase of 29%, 11%, 9% and 8% respectively in Virtual KITTI. Surprisingly, CNN model is able to produce good semantic segmentation from depth images only. The proposed networ
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發(fā)表于 2025-3-24 17:40:44 | 只看該作者
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發(fā)表于 2025-3-24 21:00:08 | 只看該作者
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發(fā)表于 2025-3-24 23:56:40 | 只看該作者
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