Embedded Files
Concept-based Learning about CI @ FUZZ-IEEE 2023
Fuzzy Logic 08132023-Marek Reformat @ FUZZ-IEEE 2023
Fuzzy Logic 08132023-Marek Reformat @ FUZZ-IEEE 2023
Evolutionary Computation 08132023-Yusuke Nojima @ FUZZ-IEEE 2023
Evolutionary Computation 08132023-Yusuke Nojima @ FUZZ-IEEE 2023
Neural Networks 08082023-Amir Pourabdollah @ FUZZ-IEEE 2023
Concept-based Learning about CI @ IEEE CEC 2023
Evolutionary Computation 07022023-Alexander Dockhorn @ IEEE CEC 2023
Neural Network 07022023-Dominik Woiwode @ IEEE CEC 2023
Concept-based Learning about CI @ 2021
Fuzzy Logic 07112021-Keeley Crockett @ FUZZ-IEEE 2021
Evolutionary Computation 07112021-Yusuke Nojima @ FUZZ-IEEE 2021
Neural Network 07112021-Amir Pourabdollah @ FUZZ-IEEE 2021
Neural Network 08162021-Naoyuki Kubota @ 2021 IEEE CIS Summer School
Tutorial on CI&AI-FML Experience and Learning Model for Advanced Driver Assistance System (ADAS)
CI&AI-FML Application to Camera Module
CI&AI-FML Application to Advanced Driver Assistance System (ADAS)
Camera Module Operation of CI&AI-FML Learning Tools
SD Card Module Operation of CI&AI-FML Learning Tools
ADAS Manual Operation of CI&AI-FML Learning Tools
ADAS Automatic of CI&AI-FML Learning Tools
Data Collection Operation of CI&AI-FML Learning Tools
CI&AI-FML Robot, MoonCar, and Learning Tools Application to ADAS
Tutorial on CI&AI-FML Experience and Learning Model for Brainwave Drone Control Experience
Track D: BCI Device Control Drone
Track D: Real-time Brain-Controlled Drone @ IEEE CEC 2023
Tutorial on CI&AI-FML Experience and Learning Model for Pre-University Student Practice
Track A.1 Human Intelligence (HI)-based Fuzzy Logic and System (HI-FLS): Construct KB & RB @ ZAI-FML Learning Platform
Track A.2 Human Intelligence (HI)-based Fuzzy Logic and System (HI-FLS): Design Blockly Program @ NUWA Lab.
Track A.3 Human Intelligence (HI)-based Fuzzy Logic and System (HI-FLS): Import Blokly Program to Robot from NUWA Lab. and Control Robot via MQTT @ ZAI-FML Learning Platform
Track B Nature-Inspired Evolution Computation (EC) and Machine Learning (EC-ML): PSO-based Machine Learning @ ZAI-FML Learning Platform
Track C.1 Experience and Practice Neural Network (NN) Applications with Google Teachable Machine and Robot: Image Data Collection and Machine Learning
Track C.2 Experience and Practice Neural Network (NN) Applications with Google Teachable Machine and Robot: AI-FML Robot Setting and the Blockly Program Design
Track C.3 Experience and Practice Neural Network (NN) Applications with Google Teachable Machine and Robot: Combine AI-FML Travel Recommendation with Robot Image Recognition
Track C.4 Experience and Practice Neural Network (NN) Applications with Google Teachable Machine and Robot: AI-FML Travel Recommendation Application with Image Recognition (Simulation)
Track F Practice and Application of CI Mini Project: AI-FML Travel Recommendation
Che-Chia Liang Introcuces Travel Recommendation Application
Page updated
Report abuse