231 to 240 of 298 Results
Apr 1, 2021
Appointment: PhD Student The datasets used in "Chromatin loop anchors predict exon usage" |
Mar 31, 2021
Appointment: Associate Professor Research topics: • Resilient CPS/IoT system functions (e.g., timing, synchronization, location, etc) • Low-power wide area networks • Thermal and energy control in data centers • Deep learning for sensing For more information, visit webpage |
Dec 21, 2020 - Zhu Shien
Zhu, Shien; Duong, H. K. Luan; Liu, Weichen, 2020, "Replication Data for: XOR-Net: An Efficient Computation Pipeline for Binary Neural Network Inference on Edge Devices", https://doi.org/10.21979/N9/XEH3D1, DR-NTU (Data), V1, UNF:6:5DOBB66c624HMnkRD7Qw9g== [fileUNF]
Accepted as a conference paper by IEEE International Conference on Parallel and Distributed Systems (ICPADS) 2020. |
Oct 28, 2020 - Bitcoin Graph Analytics
Oggier, Frederique Elise; Datta, Anwitaman, 2020, "A directed Bitcoin subgraph with 209 nodes", https://doi.org/10.21979/N9/5CFO3I, DR-NTU (Data), V1
This file contains a list of edges, specified by two Bitcoin addresses. |
Oct 26, 2020 - Yang Sheng
Yang, Sheng, 2020, "Replication Data for: SGDNet: An End-to-End Saliency-Guided Deep Neural Network for No-Reference Image Quality Assessment", https://doi.org/10.21979/N9/H38R0Z, DR-NTU (Data), V1
This repository contains the reference code for our ACM MM 2019 paper. Its GitHub link is https://github.com/ysyscool/SGDNet |
Oct 26, 2020 - Yang Sheng
Yang, Sheng, 2020, "Replication Data for: A Dilated Inception Network for Visual Saliency Prediction", https://doi.org/10.21979/N9/OIYLBK, DR-NTU (Data), V1
This repository contains the reference code for our TMM paper. The related Github link is https://github.com/ysyscool/DINet |
Oct 26, 2020
Appointment: PhD student (Graduated) |
Sep 18, 2020 - Wai Kin Adams KONG
Chen, Peng; Swarup, Pranjal; Matkowski, Wojciech Michal; Kong, Adams Wai Kin; Han, Su; Zhang, Zhihe; Rong, Hou, 2020, "Panda images dataset", https://doi.org/10.21979/N9/8CYVGF, DR-NTU (Data), V4
The data used in the study titled "A Study on Giant Panda Recognition Based on Images of a Large Proportion of Captive Pandas". |
