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8th BDCAT 2021: Leicester, United Kingdom
- BDCAT '21: 2021 IEEE/ACM 8th International Conference on Big Data Computing, Applications and Technologies, Leicester, United Kingdom, December 6 - 9, 2021. ACM 2021, ISBN 978-1-4503-9164-1
- Aimer Bhat, Heeki Park, Madhumonti Roy:
Evaluating Serverless Architecture for Big Data Enterprise Applications. 1-8 - Ilyas Ashkir, Ben Roullier, Frank McQuade, Ashiq Anjum:
3D object recognition for Virtual Reality based Digital Twins. 9-17 - Richard O. Sinnott, Zijian Wang:
Linking User Accounts across Social Media Platforms. 18-27 - Zuo Huang, Richard O. Sinnott, Qiuhong Ke:
Crowd Counting Using Deep Learning in Edge Devices. 28-37 - Changhao Bai, Peng Wu:
PRRL: Path Rotation based Knowledge Graph Representation Learning method. 38-45 - Yuanhang Xu, Peng Wu:
Multiscale Clustering Based Diffusion Representation Learning Method. 46-51 - Amirmasoud Ghiassi, Robert Birke, Lydia Y. Chen:
TrustNet: Learning from Trusted Data Against (A)symmetric Label Noise. 52-62 - Barjinder Kaur, Sajjad Dadkhah
, Pulei Xiong, Shahrear Iqbal, Suprio Ray, Ali A. Ghorbani:
Verification Based Scheme to Restrict IoT Attacks. 63-68 - Guoyi Zhao
, Tian Zhou
, Lixin Gao:
A Proactive Data-Parallel Framework for Machine Learning. 69-79 - Menuka Warushavithana, Caleb Carlson, Saptashwa Mitra, Daniel Rammer, Mazdak Arabi, F. Jay Breidt
, Sangmi Lee Pallickara, Shrideep Pallickara:
Distributed Orchestration of Regression Models Over Administrative Boundaries. 80-90 - Sheriffo Ceesay, Yuhui Lin, Adam Barker:
Benchmarking and Performance Modelling of Dataflow with Cycles. 91-100 - Zihan Yang, Richard O. Sinnott, Qiuhong Ke, James Bailey:
Individual Feral Cat Identification through Deep Learning. 101-110 - Wenhan Gao, Peng Wu, Li Pan:
Attribute Network Embedding Method based on Joint Clustering of Representation and Network. 111-119 - Kshitij Sinha, Muskan Lalit:
Comparative Analysis of Pre-Trained Deep Neural Networks for Vision-Based Security Systems on a Novel Dataset. 120-127 - Maxim Priymak, Richard O. Sinnott:
Real-Time Traffic Classification through Deep Learning. 128-133
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