Edge–Device Collaborative Deep Computing
Supports customized model partitioning for uploaded models and deployment across multiple target devices for collaborative computing under specified resource constraints.
Welcome to Crowd Intelligence with the Deep Fusion of Human, Machine and Things Open Platform!
Welcome to the Open Platform for Human–Machine–Thing Collective Intelligence Computing
More
Supports customized model partitioning for uploaded models and deployment across multiple target devices for collaborative computing under specified resource constraints.
Supports customized model compression for uploaded models to reduce model size under specified resource constraints.
On resource-constrained platforms such as microcontrollers,
we measure real-device metrics for user models under selectable hardware configurations.
Supports simulating reinforcement learning by defining actions and rewards for typical scenarios, enabling comparison across different policies.
Supports knowledge transfer using user-uploaded data,
to learn from existing knowledge and experience, cognitive structures, and action skills.
Supports discovering and applying emergent mechanisms of bio-inspired collective intelligence,
to improve the efficiency of agents in collaborative tasks.
Provides diverse open-source code downloads and supports the expansion of the developer ecosystem.
Learn moreSupports measuring model parameters, FLOPs, energy consumption, and other performance metrics for uploaded models.
Learn moreEncourages sharing and innovation, fostering an open learning community to spark creativity.
Learn more
Peking University
Tsinghua University
Fudan University
Beihang University
National University of Defense Technology
Xi'an Jiaotong University
Wuhan University
Huazhong University of Science and Technology
Sun Yat-sen University
China Machine Press
Southeast University
Northwestern Polytechnical University
Tianjin University
Tongji University
Institute of Computing Technology, Chinese Academy of Sciences
Xidian University
Jilin University
National Digital Switching System Engineering & Technological R&D Center
Institute of Computing Technology, Chinese Academy of Sciences
Chongqing University
Zhengzhou University
Beijing University of Technology
Northeast Forestry University
Xi'an University of Technology
Inner Mongolia Agricultural University
Hunan Normal University
East China University of Science and Technology
Xi'an University of Science and Technology
Shantou University
Hohai University
Jinan University
Northeast Normal University
Wuhan University of Science and Technology
Hunan University
University of Science and Technology Beijing
Harbin University of Science and Technology
North University of China
Shanghai Polytechnic University
Shandong Normal University
Xiamen University
Hunan University of Technology and Business
Nanjing University of Information Science and Technology
Peking University
Tsinghua University
Fudan University
Beihang University
National University of Defense Technology
Xi'an Jiaotong University
Wuhan University
Huazhong University of Science and Technology
Sun Yat-sen University
China Machine Press
Southeast University
Northwestern Polytechnical University
Tianjin University
Tongji University
Institute of Computing Technology, Chinese Academy of Sciences
Xidian University
Jilin University
National Digital Switching System Engineering & Technological R&D Center
Institute of Computing Technology, Chinese Academy of Sciences
Chongqing University
Zhengzhou University
Beijing University of Technology
Northeast Forestry University
Xi'an University of Technology
内蒙古农业大学
Hunan Normal University
East China University of Science and Technology
Xi'an University of Science and Technology
汕头大学
Hohai University
Jinan University
Northeast Normal University
Wuhan University of Science and Technology
Hunan University
University of Science and Technology Beijing
Harbin University of Science and Technology
North University of China
Shanghai Polytechnic University
Shandong Normal University
Xiamen University
Hunan University of Technology and Business
Nanjing University of Information Science and Technology
本书以人机物融合环境中由人、计算机、物品构成的混成群体为研究对象,提出 并阐释“人机物融合群智计算”这一概念,并探索构建其基础理论与方法体系。 既可以作为专著,为物联网、人工智能、工业互联网、智慧城市等领域的科研人员和IT从业者提供新的发展视角和相关理论、方法和技术支撑,也可以作为本科生或研究生的参考教材。
Learn more177-9583-3104
crowdhmt@mail.nwpu.edu.cn
No. 1 Dongxiang Road, Dongda Town, Chang’an District, Xi’an, Shaanxi, China
Room 501, School of Computer Science, Chang’an Campus, Northwestern Polytechnical University