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DeepEye: Resource Efficient Local Execution of Multiple Deep Vision Models using Wearable Commodity Hardware.

, , , , , and . MobiSys, page 68-81. ACM, (2017)

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Capturing Personal and Crowd Behavior with Wi-Fi Analytics., , , , , , and . WPA@MobiSys, page 43-48. ACM, (2016)On-Wearable AI to Model Human Interruptibility., , , and . MobiSys, page 520. ACM, (2018)Exploring space syntax on entrepreneurial opportunities with Wi-Fi analytics., , , , , , and . UbiComp, page 658-669. ACM, (2016)An Early Resource Characterization of Deep Learning on Wearables, Smartphones and Internet-of-Things Devices., , , , and . IoT-App@SenSys, page 7-12. ACM, (2015)Energy Efficient Scheduling for Mobile Push Notifications., , , and . EAI Endorsed Trans. Energy Web, 2 (5): e3 (2015)Demonstration Abstract: Accelerating Embedded Deep Learning Using DeepX., , , , and . IPSN, page 61:1-61:2. IEEE, (2016)Mindful interruptions: a lightweight system for managing interruptibility on wearables., , , and . WearSys@MobiSys, page 27-32. ACM, (2018)Demo: Accelerated Deep Learning Inference for Embedded and Wearable Devices using DeepX., , , , and . MobiSys (Companion Volume), page 109. ACM, (2016)DeepEye: Resource Efficient Local Execution of Multiple Deep Vision Models using Wearable Commodity Hardware., , , , , and . MobiSys, page 68-81. ACM, (2017)Sensing WiFi network for personal IoT analytics., , , , , and . IOT, page 104-111. IEEE, (2015)