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All Outputs (9)

Multiscale superpixelwise prophet model for noise-robust feature extraction in hyperspectral images. [Dataset] (2023)
Dataset
MA, P., REN, J., SUN, G., ZHAO, H., JIA, X., YAN, Y. and ZABALZA, J. 2023. Multiscale superpixelwise prophet model for noise-robust feature extraction in hyperspectral images. [Dataset]. IEEE transactions on geoscience and remote sensing [online], 61, article 5508912. Available from: https://doi.org/10.1109/tgrs.2023.3260634/mm1

In this paper, we have proposed Multiscale Superpixelwise Prophet model (MSPM), a novel spectral-spatial feature mining framework for noise-robust feature extraction and effective data classification of the HSI. First, we demonstrate that the Prophet... Read More about Multiscale superpixelwise prophet model for noise-robust feature extraction in hyperspectral images. [Dataset].

Labelled Vulnerability Dataset on Android source code (LVDAndro) to develop AI-based code vulnerability detection models. [Dataset] (2022)
Dataset
SENANAYAKE, J., KALUTARAGE, H., AL-KADRI, M.O., PIRAS, L. and PETROVSKI, A. 2023. Labelled Vulnerability Dataset on Android source code (LVDAndro) to develop AI-based code vulnerability detection models [Dataset]. Hosted on GitHub (online). Available from: https://github.com/softwaresec-labs/LVDAndro

Many of the Android apps get published without appropriate security considerations, possibly due to not verifying code or not identifying vulnerabilities at the early stages of development. This can be overcome by using an AI based model trained on a... Read More about Labelled Vulnerability Dataset on Android source code (LVDAndro) to develop AI-based code vulnerability detection models. [Dataset].

MVVA-net: a video aesthetic quality assessment network with cognitive fusion of multi-type feature–based strong generalization. [Dataset] (2022)
Dataset
LI, M., WANG, Z., REN, J. and SUN, M. 2022. MVVA-net: a video aesthetic quality assessment network with cognitive fusion of multi-type feature–based strong generalization. [Dataset]. Hosted on GitHub [online]. Available from: https://github.com/Lm0324/MVVA-Net

Most of the existing video aesthetic quality assessment datasets (as seen in Table 1) are not public, some are not large enough, which makes the trained depth model perform poorly and some are based on the professionalism of video shooting or the rat... Read More about MVVA-net: a video aesthetic quality assessment network with cognitive fusion of multi-type feature–based strong generalization. [Dataset].

Using artificial intelligence methods for systematic review in health sciences: a systematic review. [Appendices] (2022)
Dataset
BLAIZOT, A., VEETTIL, S.K., SAIDOUNG, P., MORENO-GARCIA, C.F., WIRATUNGA, N., ACEVES-MARTINS, M., LAI, N.M. and CHAIYAKUNAPRUK, N. 2022. Using artificial intelligence methods for systematic review in health sciences: a systematic review. [Appendices]. Research synthesis methods [online], 1393), pages 353-362. Available from: https://onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1002%2Fjrsm.1553&file=jrsm1553-sup-0001-supinfo.docx

Systematic reviews are fundamental to evidence-based decision making, as they use a comprehensive search and synthesis of the available literature. Such an operation usually requires a team of reviewers to evaluate thousands of articles. With the exp... Read More about Using artificial intelligence methods for systematic review in health sciences: a systematic review. [Appendices].

Effectiveness of app-delivered, tailored self-management support for adults with lower back pain-related disability: a selfBACK randomized clinical trial. [Dataset] (2021)
Dataset
SANDAL, L.F., BACH, K., ØVERÅS, C.K., WIRATUNGA, N., COOPER, K, et al. 2021. Effectiveness of app-delivered, tailored self-management support for adults with lower back pain-related disability: a selfBACK randomized clinical trial. [Dataset]. JAMA internal medicine [online], 181(10), pages 1288-1296. Available from: https://jamanetwork.com/journals/jamainternalmedicine/fullarticle/2782459#supplemental-tab

SELFBACK is an evidence-based decision support system that supports self-management of nonspecific low back pain. In specific, SELFBACK provides the user with evidence-based advice on physical activity level, strength/ flexibility exercises, and educ... Read More about Effectiveness of app-delivered, tailored self-management support for adults with lower back pain-related disability: a selfBACK randomized clinical trial. [Dataset].

Detection of morphological changes caused by chemical stress in the cyanobacterium Planktothrix agardhii using convolutional neural networks. [Dataset] (2021)
Dataset
CARLOTO, I., JOHNSTON, P., PESTANA, C.J. and LAWTON, L.A. 2021. Detection of morphological changes caused by chemical stress in the cyanobacterium Planktothrix agardhii using convolutional neural networks. [Dataset]. Science of the total environment [online], 784, article 146956. Available from: https://www.sciencedirect.com/science/article/pii/S004896972102026X#s0105

The presence of harmful algal bloom in many reservoirs around the world, alongside the lack of sanitation law/ordinance regarding cyanotoxin monitoring (particularly in developing countries), create a scenario in which the local population could pote... Read More about Detection of morphological changes caused by chemical stress in the cyanobacterium Planktothrix agardhii using convolutional neural networks. [Dataset].

Heterogeneous ensemble selection for evolving data streams. [Dataset] (2020)
Dataset
LUONG, A.V., NGUYEN, T.T., LIEW, A.W.-C. and WANG, S. 2021. Heterogeneous ensemble selection for evolving data streams. [Dataset]. Pattern recognition [online], 112, article ID 107743. Available from: https://www.sciencedirect.com/science/article/pii/S003132032030546X#sec0023

Ensemble learning has been widely applied to both batch data classification and streaming data classification. For the latter setting, most existing ensemble systems are homogenous, which means they are generated from only one type of learning model.... Read More about Heterogeneous ensemble selection for evolving data streams. [Dataset].

Walsh families of all rank-invariant classes of 3-bit pseudo-Boolean functions. [Dataset] (2016)
Dataset
CHRISTIE, L.A. 2016. Walsh families of all rank-invariant classes of 3-bit pseudo-Boolean functions. [Dataset]

This dataset was compiled as part of the following PhD thesis: CHRISTIE, L.A. 2016. The role of Walsh structure and ordinal linkage in the optimisation of pseudo-Boolean functions under monotonicity invariance. Robert Gordon University, PhD thesis. H... Read More about Walsh families of all rank-invariant classes of 3-bit pseudo-Boolean functions. [Dataset].

Generating easy and hard problems using the proximate optimality principle. [Dataset] (2015)
Dataset
MCCALL, J.A.W., CHRISTIE, L.A. and BROWNLEE, A.E.I. 2015. Generating easy and hard problems using the proximate optimality principle. [Dataset]

These data were gathered to investigate the hypothesis that coherent functions will be easy and anti-coherent functions will be hard for a hillclimber. We generated 10 coherent functions for each length on bit-strings of length 6-100 and the same num... Read More about Generating easy and hard problems using the proximate optimality principle. [Dataset].