Lan Zhang
ABSTRACT
One of the major challenges for fully enjoying the power of machine learning is the need for the high-quality labelled data. To tap-in the gold-mine of data generated by IoT devices with unprecedented volume and value, we discover and leverage the hidden connections among the multimodal data collected by various sensing devices. Different modal data can complete and learn from each other, but it is challenging to fuse multimodal data without knowing their perception (and thus the correct labels). In this work, we propose MultiSense, a paradigm for automatically mining potential perception, cross-labelling each modal data, and then improving the learning models over the set of multimodal data. We design innovative solutions for segmenting, aligning, and fusing multimodal data from different sensors. We implement our framework and conduct comprehensive evaluations on a rich set of data. Our results demonstrate that MultiSense significantly improves the data usability and the power of the learning models.
- Cao, Z., Simon, T., Wei, S.-E., and Sheikh, Y. Realtime multi-person 2d pose estimation using part affinity fields. In CVPR (2017).Google Scholar
Cross Ref
- Liu, C., Zhang, L., Liu, Z., Liu, K., Li, X., and Liu, Y. Lasagna: towards deep hierarchical understanding and searching over mobile sensing data. In Proceedings of the 22nd Annual International Conference on Mobile Computing and Networking (2016), ACM, pp. 334--347.Google ScholarDigital Library
- Ning Xiao, Panlong Yang, Y. Y. H. Z. X.-Y.-L. Motion-fi: Recognizing and counting repetitive motions with passive wireless backscattering. In INFOCOM 2018-IEEE Conference on Computer Communications, IEEE (2018), IEEE.Google ScholarCross Ref
- Simon, T., Joo, H., Matthews, I., and Sheikh, Y. Hand keypoint detection in single images using multiview bootstrapping. In CVPR (2017).Google ScholarCross Ref
- Wei, S.-E., Ramakrishna, V., Kanade, T., and Sheikh, Y. Convolutional pose machines. In CVPR (2016).Google ScholarCross Ref
Index Terms
- Poster: Cross Labelling and Learning Unknown Activities Among Multimodal Sensing Data
Recommendations
Poster: SeamFarm -- Distributed Data Analytic for Precision Agriculture based on Seamless Computing
MobiCom '19: The 25th Annual International Conference on Mobile Computing and NetworkingThis work proposes a framework for distributed data analytic for precision agriculture based on seamless computing paradigm named SeamFarm. Generally, heterogeneous nodes deployed for precision agriculture where these nodes generated an extensive amount ...
POSTER: Access Control Model for the Hadoop Ecosystem
SACMAT '17 Abstracts: Proceedings of the 22nd ACM on Symposium on Access Control Models and TechnologiesApache Hadoop is an important framework for fault-tolerant and distributed storage and processing of Big Data. Hadoop core platform along with other open-source tools such as Apache Hive, Storm, HBase offer an ecosystem to enable users to fully harness ...
POSTER: A PU Learning based System for Potential Malicious URL Detection
CCS '17: Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications SecurityThis paper describes a PU learning (Positive and Unlabeled learning) based system for potential URL attack detection. Previous machine learning based solutions for this task mainly formalize it as a supervised learning problem. However, in some ...
Comments