Outputs (1121)

A multimodel-based screening framework for C-19 using deep learning-inspired data fusion. (2024)
Journal Article
SHANKAR, A., RIZWAN, P., MEKALA, M.S., ELYAN, E., GANDOMI, A.H., MAPLE, C. and RODRIGUES, J.J.P.C. 2024. A multimodel-based screening framework for C-19 using deep learning-inspired data fusion. IEEE journal of biomedical and health informatics [online], Early Access. Available from: https://doi.org/10.1109/JBHI.2024.3400878

In recent times, there has been a notable rise in the utilization of Internet of Medical Things (IoMT) frameworks particularly those based on edge computing, to enhance remote monitoring in healthcare applications. Most existing models in this field... Read More about A multimodel-based screening framework for C-19 using deep learning-inspired data fusion..

Prompting-to-distill semantic knowledge for few-shot learning. (2024)
Journal Article
JI, H., GAO, Z., REN, J., WANG, X.-A., GAO, T., SUN, W. and MA, P. 2024. Prompting-to-distill semantic knowledge for few-shot learning. IEEE geoscience and remote sensing letters [online], 21, article 6011605. Available from: https://doi.org/10.1109/lgrs.2024.3414505

Recognizing visual patterns in low-data regime necessitates deep neural networks to glean generalized representations from limited training samples. In this paper, we propose a novel few-shot classification method, namely ProDFSL, leveraging multi-mo... Read More about Prompting-to-distill semantic knowledge for few-shot learning..

ABBD: accumulated band-wise binary distancing for unsupervised parameter-free hyperspectral change detection. (2024)
Journal Article
LI, Y., REN, J., YAN, Y., MA, P., ASSAAD, M. and GAO, Z. 2024. ABBD: accumulated band-wise binary distancing for unsupervised parameter-free hyperspectral change detection. IEEE journal of selected topics in applied earth observations and remote sensing [online], 17, pages 9880-9893. Available from: https://doi.org/10.1109/JSTARS.2024.3407212

As a fundamental task in remote sensing earth observation, hyperspectral change detection (HCD) aims to identify the changed pixels in bi-temporal hyperspectral images (HSIs). However, the water-absorption effect, poor weather conditions, noise and i... Read More about ABBD: accumulated band-wise binary distancing for unsupervised parameter-free hyperspectral change detection..

Artificial intelligence-based conversational agents used for sustainable fashion: systematic literature review. (2024)
Journal Article
HERNANDEZ MANZO, D.S., JIANG, Y., ELYAN, E. and ISAACS, J. [2024]. Artificial intelligence-based conversational agents used for sustainable fashion: systematic literature review. International journal of human-computer interaction [online], Latest Articles. Available from: https://doi.org/10.1080/10447318.2024.2352920

In the past five years, the textile industry has undergone significant transformations in response to evolving fashion trends and increased consumer garment turnover. To address the environmental impacts of fast fashion, the industry is embracing art... Read More about Artificial intelligence-based conversational agents used for sustainable fashion: systematic literature review..

HRMOT: two-step association based multi-object tracking in satellite videos enhanced by high-resolution feature fusion. (2024)
Conference Proceeding
WU, Y., ZHANG, X., LIU, Q., XUE, D., SUN, H. and REN, J. 2024. HRMOT: two-step association based multi-object tracking in satellite videos enhanced by high-resolution feature fusion. In: Ren, J., Hussain, A., Liao, I.Y. et al. (eds.) Advances in brain inspired cognitive systems: proceedings of the 13th Brain-inspired cognitive systems 2023 (BICS 2023), 5-6 August 2023, Kuala Lumpur, Malaysia. Lecture notes in computer sciences, 14374. Cham: Springer [online], pages 251-263. Available from: https://doi.org/10.1007/978-981-97-1417-9_24

Multi-object tracking in satellite videos (SV-MOT) is one of the most challenging tasks in remote sensing, its difficulty mainly comes from the low spatial resolution, small target and extremely complex background. The widely studied multi-object tra... Read More about HRMOT: two-step association based multi-object tracking in satellite videos enhanced by high-resolution feature fusion..

Underwater object detection for smooth and autonomous operations of naval missions: a pilot Dataset. (2024)
Conference Proceeding
YAN, Y., LI, Y., LIN, H., SARKER, M.M.K., REN, J. and MCCALL, J. 2024. Underwater object detection for smooth and autonomous operations of naval missions: a pilot dataset. In: Ren, J., Hussain, A., Liao, I.Y. et al. (eds.) Advances in brain inspired cognitive systems: proceedings of the 13th Brain-inspired cognitive systems 2023 (BICS 2023), 5-6 August 2023, Kuala Lumpur, Malaysia. Lecture notes in computer sciences, 14374. Cham: Springer [online], pages 113-122. Available from: https://doi.org/10.1007/978-981-97-1417-9_11

Underwater object detection is essential for ensuring autonomous naval operations. However, this task is challenging due to the complexities of underwater environments that often degrade image quality, thereby hampering the performance of detection a... Read More about Underwater object detection for smooth and autonomous operations of naval missions: a pilot Dataset..

MLM-LSTM: multi-layer memory learning framework based on LSTM for hyperspectral change detection. (2024)
Conference Proceeding
LI, Y., YAN, Y. and REN, C., LIU, Q. and SUN, H. 2024. MLM-LSTM: multi-layer memory learning framework based on LSTM for hyperspectral change detection. In: Ren, J., Hussain, A., Liao, I.Y. et al. (eds.) Advances in brain inspired cognitive systems: proceedings of the 13th Brain-inspired cognitive systems 2023 (BICS 2023), 5-6 August 2023, Kuala Lumpur, Malaysia. Lecture notes in computer sciences, 14374. Cham: Springer [online], pages 51-61. Available from: https://doi.org/10.1007/978-981-97-1417-9_5.

Hyperspectral change detection plays a critical role in remote sensing by leveraging spectral and spatial information for accurate land cover variation identification. Long short-term memory (LSTM) has demonstrated its effectiveness in capturing depe... Read More about MLM-LSTM: multi-layer memory learning framework based on LSTM for hyperspectral change detection..

Image enhancement for UAV visual SLAM applications: analysis and evaluation. (2024)
Conference Proceeding
TIAN, Y., YUE, H. and REN, J. 2024. Image enhancement for UAV visual SLAM applications: analysis and evaluation. In: Ren, J., Hussain, A., Liao, I.Y. et al. (eds.) Advances in brain inspired cognitive systems: proceedings of the 13th Brain-inspired cognitive systems 2023 (BICS 2023), 5-6 August 2023, Kuala Lumpur, Malaysia. Lecture notes in computer sciences, 14374. Cham: Springer [online], pages 51-61. Available from: https://doi.org/10.1007/978-981-97-1417-9_20.

Although simultaneous localisation and mapping (SLAM) has been widely applied in a wide range of robotics and navigation applications, its applicability is severely affected by the quality of the acquired images, especially for those in unmanned aeri... Read More about Image enhancement for UAV visual SLAM applications: analysis and evaluation..

Impact of healthy eating among residents in Aberdeen using exploratory data analysis. (2024)
Book Chapter
SALAMI, J.S. and BANO, S. 2024. Impact of healthy eating among residents in Aberdeen using exploratory data analysis. In Lee, R. (ed.) Computer and information science and engineering, volume 16. Studies in computational intelligence, 1156. Cham: Springer [online], pages 1-16. Available from: https://doi.org/10.1007/978-3-031-57037-7_1

This survey research uses Exploratory Data Analysis (EDA) to examine how the impact of healthy eating can affect Aberdeen residents and how excessive consumption of junks food can cause weight gain, raise the risk of obesity, heart disease, type 2 di... Read More about Impact of healthy eating among residents in Aberdeen using exploratory data analysis..

Decoding memes: a comprehensive analysis of late and early fusion models for explainable meme analysis. (2024)
Conference Proceeding
ABDULLAKUTTY, F. and NASEEM, U. 2024. Decoding memes: a comprehensive analysis of late and early fusion models for explainable meme analysis. In: Chua, T.-S., Ngo, C.-W., Kumar, R., Lauw, H.W. and Lee, R.K.-W. (eds.). WWW'24 companion: companion proceedings of the ACM web conference 2024, 13-17 May 2024, Singapore. New York: ACM [online], pages 1681-1689. Available from: https://doi.org/10.1145/3589335.3652504

Memes are important because they serve as conduits for expressing emotions, opinions, and social commentary online, providing valuable insight into public sentiment, trends, and social interactions. By combining textual and visual elements, multi-mod... Read More about Decoding memes: a comprehensive analysis of late and early fusion models for explainable meme analysis..