Unveiling the hidden depths: advancements in underwater image enhancement using deep learning and auto-encoders by Jaisuraj Bantupalli, Amal John Kachapilly, Sanjukta Roy, Pavithra L. K.

“…Specifically, a convolutional autoencoder is trained to learn a mapping from the distorted colors present in underwater images to their true, color-corrected counterparts. …”
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Teaching strategies in physical education: a confrontation between directive and indirective styles in volleyball learning by Bruno Vinicius Freitas da Silva, Renato Henrique dos Santos, Guilherme Rocha Savarezzi, Maurício Teodoro de Souza, Roberto Gimenez

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Self-regulation of learning in Chilean primary school students: Validation of an instrument and differences by sex and grade by Fabiola Sáez Delgado, Javier Mella Norambuena, Marcela Bizama, Joan Gatica

“…Self-regulated learning has been widely praised as a key competence for initiating and maintaining lifelong learning. …”
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High School and Undergraduate Student Volunteers as an Imperfect Solution to Machine Learning Geoscience Research Needs by Sarah E. Esenther, Neiv Gupta, Chanatip Vongkitbuncha, Mason N. Lee, Laurence C. Smith

“…Abstract The machine learning revolution presents geoscientists with exciting new opportunities for research, but is constrained by the need for large, high quality training data sets. …”
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A Machine Learning-Based Risk Prediction Model During Pregnancy in Low-Resource Settings by Kapil Tomar, Chandra Mani Sharma, Tanisha Prasad, Vijayaraghavan M. Chariar

“…The dataset utilized in this study included both the present and past medical histories and important vitals of pregnant women. …”
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Interpretable deep learning of single-cell and epigenetic data reveals novel molecular insights in aging by Zhi-Peng Li, Zhaozhen Du, De-Shuang Huang, Andrew E. Teschendorff

“…We show that the ribosomal module and inflammatory pathways would not have been discovered had we used more standard machine-learning methods. In summary, the computational deep learning framework presented here illustrates how deep learning when combined with explainable AI tools, can reveal novel biological insights into the complex process of aging.…”
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Enhancing Multi-Disease Prediction with Machine Learning: A Comparative Analysis and Hyperparameter Optimization Approach by Mariam Kili Bechir, Ferhat Atasoy

“…Although traditional methods based on statistical parameters are still important in healthcare, Machine learning (ML) algorithms offer promising results for analyzing health data. …”
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Automated data processing and feature engineering for deep learning and big data applications: A survey by Alhassan Mumuni, Fuseini Mumuni

“…In this work, we present a thorough review of approaches for automating data processing tasks in deep learning pipelines, including automated data preprocessing – e.g., data cleaning, labeling, missing data imputation, and categorical data encoding – as well as data augmentation (including synthetic data generation using generative AI methods) and feature engineering – specifically, automated feature extraction, feature construction and feature selection. …”
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Mitigating riparian buffer zone degradation through policy interventions and learnings from best practices by Aditi Majumdar, Kirti Avishek

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A Hybrid Deep Learning Model for Waste Detection and Classification Utilizing YOLOv8 and CNN by Ain Atiqa Mustapha, Sarah ‘Atifah Saruchi, Heru Supriyono, Mahmud Iwan Solihin

“…This research presents a new hybrid deep-learning model for object identification and classification. …”
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Information extraction from green channel textual records on expressways using hybrid deep learning by Jiaona Chen, Jing Zhang, Weijun Tao, Yinli Jin, Heng Fan

“…In order to extract knowledge from various records, this study presents a cutting-edge approach to extract information from textual records of failure cases in the vertical field of expressway green channel. …”
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Predicting hydrocarbon reservoir quality in deepwater sedimentary systems using sequential deep learning techniques by Xiao Hu, Jun Xie, Xiwei Li, Junzheng Han, Zhengquan Zhao, Hamzeh Ghorbani

“…Abstract This study uses advanced deep learning techniques to present an efficient and data-driven method for predicting the Hydrocarbon Reservoir Quality Index (HRQI) in deepwater carbonate systems. …”
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Problem-Oriented Learning as a Method of Developing Soft Skills Among Students of Pedagogical Specialties by Perizat Sanatbay, Guldana Smailova, Kadisha Shalgynbayeva, Marziya Asilbekova, Anar Tauekelova

“…In the context of the transformation of the modern higher education system, the supra-professional competencies (soft skills) necessary for future specialists in the humanitarian field, in particular, social educators, are of particular importance. The present study is aimed at studying the effectiveness of problem-based learning (PBL) as a method of forming key soft skills among students of the educational program “Social Pedagogy” of the L.N. …”
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Radar-Based Activity Recognition in Strictly Privacy-Sensitive Settings Through Deep Feature Learning by Giovanni Diraco, Gabriele Rescio, Alessandro Leone

“…Human activity recognition in privacy-sensitive environments, such as bathrooms, presents significant challenges due to the need for non-invasive and anonymous monitoring. …”
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Segmentation of Endothelial Cell Boundaries of Rabbit Aortic Images Using a Machine Learning Approach by Saadia Iftikhar, Andrew R. Bond, Asim I. Wagan, Peter D. Weinberg, Anil A. Bharath

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Deep Learning-Based Short Text Summarization: An Integrated BERT and Transformer Encoder–Decoder Approach by Fahd A. Ghanem, M. C. Padma, Hudhaifa M. Abdulwahab, Ramez Alkhatib

“…To overcome these challenges, this paper introduces a deep learning framework for automated short text summarization on Twitter. …”
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Innovative machine learning approaches for complexity in economic forecasting and SME growth: A comprehensive review by Mustafa I. Al-Karkhi, Grzegorz Rza̧dkowski

“…This paper reviews recent advancements in economic regression and SME growth forecasts, with a focus on the application of machine learning (ML) techniques. Specifically, the findings highlight that the integration of ensemble methods and deep learning models has achieved significant improvements in prediction accuracy, while interpretability tools such as SHAP and LIME enhance transparency and user trust. …”
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Developing and evaluating the fidelity of virtual reality-artificial intelligence (VR-AI) environment for situated learning by April Tan, April Tan, Michael C. Dorneich, Elena Cotos

“…This study focuses on developing, operationalizing, and evaluating the fidelity of the VR-AI environment across four key dimensions: physical, functional, psychological, and social fidelity.MethodsTwenty participants tested the environment, completing two learning tasks: engaging with poster presenters and reflecting with a major professor. …”
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Chronic liver disease detection using ranking and projection-based feature optimization with deep learning by Sumaiya Noor, Salman A. AlQahtani, Salman Khan

“…This study presents a novel and efficient learning method to identify liver patients accurately. …”
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CLEAR: Multimodal Human Activity Recognition via Contrastive Learning Based Feature Extraction Refinement by Mingming Cao, Jie Wan, Xiang Gu

“…With the development of artificial intelligence (AI) and Internet of Things (IoT), sensor-based HAR has gained increasing attention and presents great advantages to existing work. Relying solely on existing labeled data may not adequately address the challenge of ensuring the model’s generalization ability to new data. …”
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