Extracting Learning Data From Handwritten Notes: A New Approach to Educational Data Analysis Based on Image Segmentation and Generative AI by Yunyu Zhou, Cheng Tang, Atsushi Shimada

“…This research contributes to educational technology and data mining by introducing an automated, scalable method that supports more personalized and effective educational strategies.…”
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Facial Feature Recognition with Multi-task Learning and Attention-based Enhancements by M. Rohani, H. Farsi, S. Mohamadzadeh

“…This paper proposes a novel multi-task learning (MTL) model that leverages the powerful Efficient-Net architecture and incorporates attention-based learning with two key innovations. …”
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Multi-Task Water Quality Colorimetric Detection Method Based on Deep Learning by Shenlan Zhang, Shaojie Wu, Liqiang Chen, Pengxin Guo, Xincheng Jiang, Hongcheng Pan, Yuhong Li

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Transformer-based multi-task learning for table tennis motion feature recognition by Tianfang Ma

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Multi-Task Spiking Neural Network for Simultaneous Vapor Recognition and Concentration Estimation by Pedro Sartori Locatelli, Salma Ait Fares, Dalton Martini Colombo, Kamal El-Sankary, Michael S. Freund

“…Neural networks have been instrumental in advancing machine olfaction systems, greatly enhancing their ability to process olfactory information. As the drive to integrate sensing and signal processing on chip continues, recent advancements emphasize the need for simple yet efficient pattern recognition systems. …”
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An earned presence: studying the effect of multi-task improvisation systems on cognitive and learning capacity by Pil Hansen, Robert J. Oxoby

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TFCNet: A Hybrid Architecture for Multi-Task Restoration of Complex Underwater Optical Images by Shengya Zhao, Xiufen Ye, Xinkui Mei, Shuxiang Guo, Haibin Qi

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Real-Time Autonomous Driving: A Unified Single-Stage Multi-Task Network Architecture by S. Raghavendra, Rajalekshmi Kishore, S. K. Abhilash, Venu Madhav Nookala, Manish Varun Yadav

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Multi-task reinforcement learning and explainable AI-Driven platform for personalized planning and clinical decision support in orthodontic-orthognathic treatment by Zhiyuan Li, Liwei Wang

“…Abstract This study presents a novel clinical decision support platform for orthodontic-orthognathic treatment that integrates multi-task reinforcement learning with explainable artificial intelligence. …”
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A multi task learning framework using DeBERTa and BWO optimization for enhancing long term english vocabulary memory by Jiasheng Zhu

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Automatic GPR detection of grouting defects behind the tunnel shield segments based on wavelet coherence analysis combined with modified Res-RCNN by Dengyi Wang, Ming Peng, Liu Liu, Xiongyao Xie, Zhenming Shi, Yaoying Liang, Jian Shen, Qiyu Wu

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Discovering the Hidden Work of Commodified Care: The Case of Early Childhood Educators by Frances Press, Michael Bittman, Linda Joan Harrison, Judith E. Brown, Sandie Wong, Megan Gibson

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An Improved YOLOP Lane-Line Detection Utilizing Feature Shift Aggregation for Intelligent Agricultural Machinery by Cundeng Wang, Xiyuan Chen, Zhiyuan Jiao, Shuang Song, Zhen Ma

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Emotion recognition and interaction of smart education environment screen based on deep learning networks by Zhao Wei, Qiu Liguo

“…Smart education environments combine technologies such as big data, cloud computing, and artificial intelligence to optimize and personalize the teaching and learning process, thereby improving the efficiency and quality of education. …”
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The PRIME model: a management solution in academic medicine by Gert J. van Zyl, Maria Nel

“…The second part of the empirical study was the Delphi process, which involved six experts from the areas of management, health management, and education. …”
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Intelligence data acquisition based on embedded system in Chinese cuisine cooker (CCICR V1.0) by Jianbao Zhang, Deyi Wang, Shiping Bao, Xin Chang, Yi Liang

“…These sensors facilitate the intelligent collection of data related to dishes, ingredients, and the movements of cookware throughout the cooking process. To ensure efficient data acquisition and storage, CCICR-V1.0 employs a multi-task data buffering storage method that effectively allocates CPU resources. …”
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Performance Comparison of Prediction of Hydraulic Jump Length Under Multiple Neural Network Models by Ziyuan Xu, Zirui Liu, Yingzi Peng

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The analysis of acquisition system for electronic traffic signal in smart cities based on the internet of things by Yue Ma, Chenglong Wang, Tianlei Fu, Ziting Meng

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Preprocessing and Denoising Techniques for Electrocardiography and Magnetocardiography: A Review by Yifan Jia, Hongyu Pei, Jiaqi Liang, Yuheng Zhou, Yanfei Yang, Yangyang Cui, Min Xiang

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Convolutional Neural Networks for Automatic Identification of Individuals at Terrestrial Terminals by Darwin Yarango-Farro, Alex Mondragon-Fernandez, Heber I. Mejia-Cabrera, Juan Arcila-Diaz

“…To optimize the search process during real-time identification, the embeddings were transferred to FAISS, a library optimized for similarity search in large-scale datasets. …”
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