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Figure 1 from Thinking Fast and Slow: An Approach to Energy-Efficient Human Activity Recognition on Mobile Devices

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Figure 1: Detecting begin and end of a trip relative to a significant place: Use cell-id patterns for “intuitive” detection when possible, and use GPS/WiFi for “deliberate” detection when necessary. Energy saving is achieved when a user visits the same places and repeats the same trips and accordingly the system works in the intuition mode. - "Thinking Fast and Slow: An Approach to Energy-Efficient Human Activity Recognition on Mobile Devices"

Figure 1 from Thinking Fast and Slow: An Approach to Energy-Efficient Human Activity Recognition on Mobile Devices

Biosensors, Free Full-Text

Figure 1 from Thinking Fast and Slow: An Approach to Energy-Efficient Human Activity Recognition on Mobile Devices

AI is about to completely change how you use computers

Figure 1 from Thinking Fast and Slow: An Approach to Energy-Efficient Human Activity Recognition on Mobile Devices

Science analogies - Science-Education-Research

Figure 1 from Thinking Fast and Slow: An Approach to Energy-Efficient Human Activity Recognition on Mobile Devices

The convergence of lean management and additive manufacturing: Case of manufacturing industries - ScienceDirect

Figure 1 from Thinking Fast and Slow: An Approach to Energy-Efficient Human Activity Recognition on Mobile Devices

Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges, and Opportunities

Figure 1 from Thinking Fast and Slow: An Approach to Energy-Efficient Human Activity Recognition on Mobile Devices

Routescore: Punching the Ticket to More Efficient Materials Development

Figure 1 from Thinking Fast and Slow: An Approach to Energy-Efficient Human Activity Recognition on Mobile Devices

Deep learning for sensor-based human activity recognition, by Wisdom D'Almeida

Figure 1 from Thinking Fast and Slow: An Approach to Energy-Efficient Human Activity Recognition on Mobile Devices

Artificial Intelligence: Thinking, fast(er) and slow

Figure 1 from Thinking Fast and Slow: An Approach to Energy-Efficient Human Activity Recognition on Mobile Devices

Designing Metasurfaces for Efficient Solar Energy Conversion

Figure 1 from Thinking Fast and Slow: An Approach to Energy-Efficient Human Activity Recognition on Mobile Devices

Frontiers Technological Approach to Mind Everywhere: An Experimentally-Grounded Framework for Understanding Diverse Bodies and Minds

Figure 1 from Thinking Fast and Slow: An Approach to Energy-Efficient Human Activity Recognition on Mobile Devices

PDF] Human Activity Recognition Based on Improved Bayesian Convolution Network to Analyze Health Care Data Using Wearable IoT Device

Figure 1 from Thinking Fast and Slow: An Approach to Energy-Efficient Human Activity Recognition on Mobile Devices

Sensors, Free Full-Text

Figure 1 from Thinking Fast and Slow: An Approach to Energy-Efficient Human Activity Recognition on Mobile Devices

Human Activity Recognition With Neural Networks 👥

Figure 1 from Thinking Fast and Slow: An Approach to Energy-Efficient Human Activity Recognition on Mobile Devices

Prediction during language comprehension: what is next?: Trends in Cognitive Sciences

Figure 1 from Thinking Fast and Slow: An Approach to Energy-Efficient Human Activity Recognition on Mobile Devices

5G-enabled contactless multi-user presence and activity detection for independent assisted living