Results 91 to 100 of about 68,922 (259)

Self-assessment in machines boosts human Trust

Frontiers in Robotics and AI
Low trust in autonomous systems remains a significant barrier to adoption and performance. To effectively increase trust in these systems, machines must perform actions to calibrate human trust based on an accurate assessment of both their capability and
Dana Warmsley, Krishna Choudhary , Jocelyn Rego , Emma Viani , Praveen K. Pilly    +4 more
doaj   +1 more source

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

Advanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena, J. Terence Blaskovits, Kun‐Han Lin, Denis Andrienko   +3 more
wiley   +1 more source

Human Machine Collaboration for Multiple Object Tracking in Videos

, 2023
While modern computer vision solutions have achieved impressive strides, the level of accuracy for many complicated tasks is still not on par with human intelligence. In particular, humans are incredibly adept at generalizing to novel scenarios.
Anjum, Samreen
core   +2 more sources

How human–machine collaboration fuels employees' digital creativity: the serial mediating roles of technology acceptance and positive emotion

Frontiers in Psychology
Against the backdrop of AI-driven digital transformation, digital creativity has emerged as a critical driver of corporate innovation. Consequently, investigating the mechanisms through which human–machine collaboration influences employees‘ digital ...
Lijun Xia, Zhouyan Zheng, Binlin Si, Huabin Wu, Huabin Wu, Jiali Zhu   +5 more
doaj   +1 more source

Phase Engineering of Nanomaterials (PEN): Evolution, Current Challenges, and Future Opportunities

Advanced Materials, EarlyView.
This review summarizes the synthesis, phase transition, advanced characterization spanning ex situ to in situ and operando techniques, and diverse applications of phase engineering of nanomaterials (PEN). It further outlines key challenges and future opportunities, such as phase stability, architecture control, and artificial intelligence (AI)‐driven ...
Ye Chen, Zhanxi Fan, Jingjie Ge, Qiyuan He, Zhuangchai Lai, Jiawei Liu, Chaoliang Tan, Hua Zhang   +7 more
wiley   +1 more source

KGMM -- A Maturity Model for Scholarly Knowledge Graphs based on Intertwined Human-Machine Collaboration

, 2022
Knowledge Graphs (KG) have gained increasing importance in science, business and society in the last years. However, most knowledge graphs were either extracted or compiled from existing sources.
Karras, Oliver, Hussein, Hassan, Oelen, Allard, Auer, Sören   +3 more
core   +1 more source

Weaving Intelligence: Thermally Drawn Multimaterial Fibers Toward AI‐Enabled Smart Textiles

Advanced Materials, EarlyView.
Thermally drawn multimaterial fibers are rapidly advancing as intelligent structural units for next‐generation smart textiles. Integrating multimaterial architectures with neuromorphic and spiking‐neural‐network principles enables fabrics that can sense, compute, and adapt autonomously.
Vuong Dinh Trung, Jiaxiang Yi, Hieu Nguyen‐Duc, Tien Nu Hoang Lo, Weili Zhao, Chaoqun Dong, Fabien Sorin, Baris Caglar, Lei Wei, Tung Nguyen‐Dang   +9 more
wiley   +1 more source

Designing Computer Agents with Personality to Improve Human-Machine Collaboration in Complex Systems

, 2007
The dynamic nature of complex systems and the overwhelming amount of data that must be handled by human operators requires the development of smart systems that augment human capabilities. For these systems human-agent collaboration is part of the system
Prabhala, Sasanka V.
core   +1 more source

Enhancing high-school dropout identification: a collaborative approach integrating human and machine insights

Discover Education
Despite its proven success in various fields such as engineering, business, and healthcare, human–machine collaboration in education remains relatively unexplored.
Okan Bulut, Tarid Wongvorachan, Surina He, Soo Lee   +3 more
doaj   +1 more source

Extracting Technicians' Skills for Human-Machine Collaboration in Aircraft Assembly. [PDF]

Biomimetics (Basel), 2023
Tian Y, Li J, Dan J, Shu Y, Liu C, Li R, Liu S.   +6 more
europepmc   +1 more source