dataset (we will refer to this technique as a centralized model) to validate the efficiency of SL technique as a decentralized learning technique. For this purpose, we used 80% of the Duke dataset for training and the remaining 20% as an internal testing cohort. The UKA dataset was ...
and mobile museum guides. The system is evaluated using a music dataset, and it is shown to outperform typical state-of-the-art single and multi-objective algorithms in terms of precision, novelty, and coverage. The approach aims to find the best compromise between multiple objectives to provide...
Vinutha H, Poornima B, Sagar B (2018) Detection of outliers using interquartile range technique from intrusion dataset. In: Information and decision sciences: proceedings of the 6th International conference on FICTA. Springer, New York, pp 511–518 Amador J, Melo Gouveia C, Pimenta AC (2023)...
Additionally, HSPSO is applied to feature selection for the UCI Arrhythmia dataset, resulting in a high-accuracy classification model that outperforms traditional methods. These findings establish HSPSO as an effective solution for complex optimization and feature selection tasks....
The proposed model was verified using a public COVID-19 radiology dataset and a public COVID-19 lung CT scan dataset. The results show that the model has made significant progress, with the false positive rate reduced to 11.3% and 7.5%, and the area under the...
weighted mean absolute percentage error (WMAPE). All the developed models forPs-ES had anRsignificantly > 0.8 for the overall dataset. However, ANN-MPA excelled in yielding highRvalues for training dataset (TrD), testing dataset (TsD), and validation dataset (VdD). This model also ...
In this study, we developed an innovative survival prediction framework known as SwarmDeepSurv that can predict survival in different cancer types using a large multicenter radiomics dataset. Three well-regarded SI algorithms have been integrated with the deep survival network. We formulated four differ...
As the basic model for very large scale integration (VLSI) routing, the Steiner minimal tree (SMT) can be used in various practical problems, such as wire length optimization, congestion, and time delay estimation. In this paper, a novel particle swarm optimization (PSO) algorithm based on ...
End-to-end classification using deep learning frameworks requires a large amount of data, which is often unavailable in HAR tasks, where there is a large number of classes in the dataset with very few samples belonging to each class. This hinders the optimal performance of CNN models. Also, ...
Autonomous environment-adaptive microrobot swarm navigation enabled by deep learning-based real-time distribution planning (dataset). Figshare https://doi.org/10.6084/m9.figshare.19149779.v1 (2022). Yang, L. et al. Autonomous environment-adaptive microrobot swarm navigation enabled by deep learning-...