Titlebook: Advances in Artificial Intelligence in Manufacturing; Proceedings of the 1 Achim Wagner,Kosmas Alexopoulos,Sotiris Makris Conference procee

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書目名稱Advances in Artificial Intelligence in Manufacturing影響因子(影響力)




書目名稱Advances in Artificial Intelligence in Manufacturing影響因子(影響力)學(xué)科排名




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書目名稱Advances in Artificial Intelligence in Manufacturing網(wǎng)絡(luò)公開度學(xué)科排名




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書目名稱Advances in Artificial Intelligence in Manufacturing被引頻次學(xué)科排名




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書目名稱Advances in Artificial Intelligence in Manufacturing年度引用學(xué)科排名




書目名稱Advances in Artificial Intelligence in Manufacturing讀者反饋




書目名稱Advances in Artificial Intelligence in Manufacturing讀者反饋學(xué)科排名

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全國(guó)性

On Bringing Fault Detection to Skill-Based Productionill model. Finally, the elaborated model is prototypically implemented in a realistic demonstration environment to come up with a proof of concept. Since it is difficult to directly model faulty behavior of Cyber-Physical Production Modules in flexible production their nominal behavior during the ex

Traumatic-Grief

Towards an Advanced Artificial Intelligence Architecture Through Asset Administration Shell and Indu. The article also explores specific Artificial Intelligence technologies with a wide application in industrial environments. In particular, the study has focused on research into Low/No Code, Explainability (XAI) tools and incremental learning algorithms. The contributions of this paper are summari

不給啤

Detection of Rare Fault Cases for Mobile Robot Applicationsg special knowledge of the internal system behavior. The procedure was implemented and tested on a mobile robot for factory-internal transport processes. With little training data, a binary classification for elementary fault detection. The method can easily be adapted to other cases of dynamical sy

執(zhí)

Vertical

Enhancing Object Detection Performance for Small Objects Through Synthetic Data Generation and Propon. This paper discusses the effects of a simple proportional class-balancing technique, to enable better anchor matching of the OD models. A comparison was carried out on the performances of the SOTA OD models: YOLOv5, YOLOv7 and SSD, for combinations of real and synthetic datasets within an industr

含鐵

上流社會(huì)

印第安人

Use of Artificial Intelligence at the Level of Manufacturing Processesexamples from both conventional and non-conventional processes are considered, as well as focused illustrations of the possibilities that AI technologies can offer. In addition, the different manufacturing attributes, as guided by different strategies, are discussed in the context of the aforementio