...Ibtissam Amalou; Oumaima Anzal; Naoual Mouhni; Abdelmounaim Abdali Purpose This paper’s purpose is to enhance multivariate time series forecasting accuracy by introducing a novel preprocessing step: leveraging advanced image deep learning denoising models via a transfer learning approach. We...

... Privacy preservation Transfer learning Semisupervised learning Differential privacy Knowledge distillation Distribute model National Key R\&D Program No.2024YFB3310202 Key R&D plan of Jilin Province No. 20250201076GX Funding: The work was supported...

... and contextual semantic representation-based clickbait detection approach employing transfer learning. This method can modify the semantic representation of each word based on context and assist the model in more precisely interpreting the original meaning of news articles. Clickbait detection is a field...

... social media played during the Hirak. Results revealed that most individuals had a positive attitude toward the Hirak. Moreover, the presented experiments provided important insights into the possible use of both basic machine learning and transfer learning models to analyze SA of Algerian text datasets...

... (Aone et al., 1998), machine learning (Kambhatla, 2004) and open relation extraction (Xu et al., 2015). 17 11 2020 10 02 2021 16 03 2021 © Emerald Publishing Limited 2021 Emerald Publishing Limited Licensed re-use rights only Transfer learning...

...Chanattra Ammatmanee; Lu Gan Purpose Because of the fast-growing digital image collections on online platforms and the transfer learning ability of deep learning technology, image classification could be improved and implemented for the hostel domain, which has complex clusters of image contents...

... classifying the lesions as melanoma and non-melanoma. Design/methodology/approach In this work, a transfer learning (TL) framework Transfer Constituent Support Vector Machine (TrCSVM) is designed for melanoma classification based on feature-based domain adaptation (FBDA) leveraging the support vector...