Advanced topics in mobile and social computing (AToMSC) (Winter 2021/2022): Difference between revisions

Jump to navigation Jump to search
Line 34: Line 34:


==List of Papers ==
==List of Papers ==
1. Lightweight and Robust Representation of Economic Scales from Satellite Imagery [https://ojs.aaai.org/index.php/AAAI/article/download/5379/5235]
2. AutoML for Video Analytics with Edge Computing [https://ieeexplore.ieee.org/abstract/document/9488704]
3. Source Compression with Bounded DNN Perception Loss for IoT Edge Computer Vision [https://dl.acm.org/doi/10.1145/3300061.3345448]
4. NN-Meter: Towards Accurate Latency Prediction of Deep-Learning Model Inference on Diverse Edge Devices [https://dl.acm.org/doi/10.1145/3458864.3467882]
5. Reducto: On-Camera Filtering for Resource-Efficient Real-Time Video Analytics [https://dl.acm.org/doi/10.1145/3387514.3405874]
6. Deep Interest Network for Click-Through Rate Prediction [https://arxiv.org/pdf/1706.06978.pdf]
7. Energy-Efficient 3D Vehicular Crowdsourcing For Disaster Response by Distributed Deep Reinforcement Learning [https://dl.acm.org/doi/pdf/10.1145/3447548.3467070]
8.


==Schedule==
==Schedule==
540

edits

Navigation menu