| date accessioned | 2022-08-18T12:52:39Z | |
| date available | 2022-08-18T12:52:39Z | |
| date copyright | 6/27/2022 12:00:00 AM | |
| date issued | 2022 | |
| identifier issn | 1530-9827 | |
| identifier other | jcise_22_5_050301.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4287018 | |
| description abstract | As envisioned by Industry 4.0, the next generation of smart factories and warehouses will highly depend on the collaboration between human and artificial intelligence (AI). This symbiotic partnership can augment human capabilities by providing suggestions, assistance, and explanations as needed—or can utilize direct or indirect human feedbacks in a human-in-the-loop learning framework to enhance AI learning capabilities. This Special Section aims to harvest the latest efforts in fundamental methodologies as well as their applications in human–AI partnership with specific applications for next-generation factories encompassing the design process to manufacturing, production, and inspection. | |
| publisher | The American Society of Mechanical Engineers (ASME) | |
| title | Special Issue: Symbiotic Human–Artificial Intelligence Partnership for Next-Generation Factories | |
| type | Journal Paper | |
| journal volume | 22 | |
| journal issue | 5 | |
| journal title | Journal of Computing and Information Science in Engineering | |
| identifier doi | 10.1115/1.4054673 | |
| journal fristpage | 50301-1 | |
| journal lastpage | 50301-2 | |
| page | 2 | |
| tree | Journal of Computing and Information Science in Engineering:;2022:;volume( 022 ):;issue: 005 | |
| contenttype | Fulltext | |