A joint learning method for low-light facial expression recognition by Yuanlun Xie, Jie Ou, Bihan Wen, Zitong Yu, Wenhong Tian

Subjects: “…Cross high- and low-level learning…”
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Similarity Learning and Generalization with Limited Data: A Reservoir Computing Approach by Sanjukta Krishnagopal, Yiannis Aloimonos, Michelle Girvan

“…We investigate the ways in which a machine learning architecture known as Reservoir Computing learns concepts such as “similar” and “different” and other relationships between image pairs and generalizes these concepts to previously unseen classes of data. …”
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Usability of Computer-Aided Translation Software Based on Deep Learning Algorithms by Junjun Liu

“…By observing, recording, and analyzing user behavior and related data, the five attributes of usability can be learned and memorable. The experiments show that the effect of this study on computer-aided software with the help of deep learning knowledge can produce good results, and the robustness and scalability of the software have been enhanced, increasing the competitiveness of the software itself in translation software.…”
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Document-Level Neural TTS Using Curriculum Learning and Attention Masking by Sung-Woong Hwang, Joon-Hyuk Chang

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The transition of online into limited English learning-teaching in the rural area context by Amira Wahyu Anditasari, Siti Kholija Sitompul

“… The Covid-19 pandemic has started to decrease, thus many schools in Indonesia have switched their learning activity from online to limited offline learning teaching. …”
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The role of lecturer discipline on student interests: motivation to learn as intervening variable by Man Yany, Djoko Soelistya, Eva Decembrianita, Rahmat Agus Samtoso, Mu’minatur Sholichah

Subjects: “…lecturer discipline, learning motivation, learning interest…”
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Potential for Vertical Heterogeneity Prediction in Reservoir Basing on Machine Learning Methods by Hongqing Song, Shuyi Du, Ruifei Wang, Jiulong Wang, Yuhe Wang, Chenji Wei, Qipeng Liu

“…With the rapid development of computer technology, some machine learning methods have begun to gradually integrate into the petroleum industry and have achieved some achievements, whether in conventional or unconventional reservoirs. …”
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Plant Disease Identification Based on Deep Learning Algorithm in Smart Farming by Yan Guo, Jin Zhang, Chengxin Yin, Xiaonan Hu, Yu Zou, Zhipeng Xue, Wei Wang

“…Finally, the segmented leaves are input into the transfer learning model and trained by the dataset of diseased leaves under simple background. …”
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Machine Learning–Based Predictive Farmland Optimization and Crop Monitoring System by Marion Olubunmi Adebiyi, Roseline Oluwaseun Ogundokun, Aneoghena Amarachi Abokhai

“…This study provided a machine learning–aided mobile system for farmland optimization, using various inputs such as location, crop type, soil type, soil pH, and spacing. …”
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Federated Learning-Based Load Forecasting for Energy Aggregation Service Providers by HUANG Yichuan, SONG Yuhui, JING Zhaoxia

Subjects: “…energy aggregation service provider|load forecasting|federated learning|data privacy|neural network…”
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Simulation-based learning and digital tools. A trial for Pharmacy Services by Fabrizio Bracco, Maria Carola Morozzo della Rocca, Federica Delprino, Silvia Pregaglia

“…The essay deals with the simulation method as an established tool in learning medical disciplines, declining it in an unprecedented scenario such as pharmaceuticals and experimenting with its digitisation. …”
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Development of Pop-Up Book Media in Science Learning for Elementary School by Rhamdani Rhamdani, Zaka Hadikusuma Ramadan

“… This research aims to develop learning media in the form of Pop-Up Book media during offline learning activities. …”
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Study approaches mediate associations between learning environment and academic performance by Tore Bonsaksen, Amayra Tannoubi, Linda Stigen, Astrid Gramstad, Tove Carstensen, Gry Mørk

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How Interpretable Machine Learning Can Benefit Process Understanding in the Geosciences by Shijie Jiang, Lily‐belle Sweet, Georgios Blougouras, Alexander Brenning, Wantong Li, Markus Reichstein, Joachim Denzler, Wei Shangguan, Guo Yu, Feini Huang, Jakob Zscheischler

Subjects: “…machine learning…”
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Performance of Quantum Annealing Machine Learning Classification Models on ADMET Datasets by Hadi Salloum, Kamil Sabbagh, Vladislav Savchuk, Ruslan Lukin, Osama Orabi, Marat Isangulov, Manuel Mazzara

“…The advancement of quantum annealers has spurred experimental demonstrations and intensified research interest, particularly in quantum machine learning. However, the application of quantum annealing in machine learning remains limited due to the lack of conclusive performance evaluations on real-world datasets. …”
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An Intelligent Optimization Strategy Based on Deep Reinforcement Learning for Step Counting by Zhoubao Sun, Pengfei Chen, Xiaodong Zhang

“…To solve the problems that the existing algorithms use threshold to filter noise, and the parameters cannot be updated in time, an intelligent optimization strategy based on deep reinforcement learning is proposed. In this study, the counting problem is transformed into a serialization decision optimization. …”
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Challenges with reinforcement learning model transportability for sepsis treatment in emergency care by Peter C. Nauka, Jason N. Kennedy, Emily B. Brant, Matthieu Komorowski, Romain Pirracchio, Derek C. Angus, Christopher W. Seymour

“…Abstract Pivotal moments in sepsis care occur in the emergency department (ED), however, and it is unclear whether ED data is adequate to inform reinforcement learning (RL) models. We evaluated the early opportunity for the AI Clinician, a validated ICU-based RL-model, as a use case. …”
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Risk factors and machine learning prediction models for intrahepatic cholestasis of pregnancy by Yingchun Ren, Xiaoying Shan, Gengchao Ding, Ling Ai, Weiying Zhu, Ying Ding, Fuzhou Yu, Yun Chen, Beijiao Wu

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Enhanced Neural Architecture for Real-Time Deep Learning Wavefront Sensing by Jianyi Li, Qingfeng Liu, Liying Tan, Jing Ma, Nanxing Chen

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Fusion-Decomposition Pan-Sharpening Network With Interactive Learning of Representation Graph by Yunxuan Tang, Xue Wang, Peng Liu, Tong Li

Subjects: “…Deep learning (DL)…”
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