集聚成团
发表于 2025-3-28 17:20:26
Paul I. Schneiderman,Marc E. Grossman One of the greatest challenges in this area is to ensure that the machine learning model is up-to-date and easily and effectively deployed to all smart systems that rely on it. However, the rapid changes, or drifts in the data can have a serious effect on the accuracy of the model, leading to unfor
DAMN
发表于 2025-3-28 21:01:03
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FIR
发表于 2025-3-28 23:09:06
Paul I. Schneiderman,Marc E. Grossmangically rich language. We applied BERTopic with three multilingual embedding models on two levels of text preprocessing (partial and full) to evaluate its performance on partially preprocessed short text in Serbian. We also compared it to LDA and NMF on fully preprocessed text. The experiments were
黄瓜
发表于 2025-3-29 04:08:45
Paul I. Schneiderman,Marc E. Grossmand HUD is to help drivers with the monitoring of the environment when operating a conditionally automated vehicle, and the transiting between different levels of automation. This paper presents the perceived usability, user experience, and acceptance of such an automotive telematics solution. The hig
打谷工具
发表于 2025-3-29 08:02:39
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tattle
发表于 2025-3-29 11:42:04
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罗盘
发表于 2025-3-29 19:05:29
Digital Technologies to Support the Decision-Making Process for Dental Implants Treatment Planningcepts and techniques of the implant dentistry area, image processing and intelligent systems systematize the determination of the best implants for multiple failures and the planning of the dental implant process. The preliminary results demonstrate the solution’s potential in finding the best solution for planning the dental implant process.
障碍
发表于 2025-3-29 22:49:36
Comparison of Deep Learning Algorithms for Facial Keypoints Detection in facial keypoints detection. While the more complex custom Neural Network model achieved high accuracy in facial keypoints identification, the simpler custom Neural Network model could not achieve high performance.
Ebct207
发表于 2025-3-30 01:53:12
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nullify
发表于 2025-3-30 06:43:55
Paul I. Schneiderman,Marc E. Grossmanrt of Edge-Cloud-based Smart Agriculture System. To support this architecture, a prototype system that provides a machine learning model as a service in the agricultural domain is developed and tested.