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Deposit, archive and share your final research data in DR-NTU (Data)

DR-NTU (Data) is for research data deposit. For research paper deposits, please use DR-NTU.

Mission: DR-NTU (Data) curates, stores, preserves, makes available and enables the download of digital data generated by the NTU research community. The repository develops and provides guidance for managing, sharing, and reusing research data to promote responsible data sharing in support of open science and research integrity.

Who can deposit? NTU faculty, research staff and students.

What can be deposited? Final, non-sensitive research data from projects carried out at NTU. The uploaded content must not infringe upon the copyrights or other intellectual property rights, and must be void of all identifiable information.

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Useful links: FAQs | Collection Guidelines | NTU Research Data Management | General terms of use and Privacy policy

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68,851 to 68,860 of 73,632 Results
Li Gen(Nanyang Technological University)
Apr 9, 2020School of Civil and Environmental Engineering (CEE)
Rei Kinjo(Nanyang Technological University)
Rei Kinjo logo
Apr 8, 2020School of Chemistry, Chemical Engineering and Biotechnology (CCEB)
Research topics: • Novel bonding and structural paradigms • Stable version of transient species • Catalysis
Thermal Image Guided Upsampling
Apr 6, 2020 - Teerawat Piriyatharawet
Piriyatharawet, Teerawat, 2020, "Thermal Image Guided Upsampling", https://doi.org/10.21979/N9/9JG8D3, DR-NTU (Data), V1, UNF:6:IuGM51Q8N4QLGePoc6I4EA== [fileUNF]
A low-resolution thermal imaging sensor becomes more affordable and is widely used in home applications. However, in order to understand detailed activities, a high-resolution thermal image is required. In this paper, we present an unsupervised deep learning framework for joint u...
arch.py
Apr 6, 2020 - Thermal Image Guided Upsampling
Python Source Code - 7.7 KB - MD5: b95532745ea068a40b1242d695d92093
arch_v1.py
Apr 6, 2020 - Thermal Image Guided Upsampling
Python Source Code - 6.4 KB - MD5: 9e74acf36027e7aec3d775a097aad9fe
box_filter.py
Apr 6, 2020 - Thermal Image Guided Upsampling
Python Source Code - 973 B - MD5: 9b300ce59e2376ce4d334ff6c81c5b73
dataset.py
Apr 6, 2020 - Thermal Image Guided Upsampling
Python Source Code - 4.2 KB - MD5: 75168a4a7a38d05b72ead47d6507a223
predict.py
Apr 6, 2020 - Thermal Image Guided Upsampling
Python Source Code - 7.2 KB - MD5: a23364b8e85675c094d5716b4cfaaa65
resize_img.py
Apr 6, 2020 - Thermal Image Guided Upsampling
Python Source Code - 827 B - MD5: 9fdbf6ba9561025c39f6486e81394f14
seg_images_traing.tab
Apr 6, 2020 - Thermal Image Guided Upsampling
Tabular Data - 182.1 KB - 2 Variables, 2869 Observations - UNF:6:IuGM51Q8N4QLGePoc6I4EA==
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