Estimation of physico-chemical properties of soil using machine learning by Patience Chizoba Mba, Opegbemi Matthias Busoye, John Temitope Ajayi, Judith Nkechinyere Njoku, Cosmas Ifeanyi Nwakanma, Senorpe Asem-Hiablie, Rammohan Mallipeddi, Tusan Park, Daniel Dooyum Uyeh

“…Alternatives to traditional soil quality estimation methods, often costly and inaccessible in resource-poor regions, are needed. …”
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MentalAId: an improved DenseNet model to assist scalable psychosis assessment by Muxi Li, Farong Liu, Fei Du, Guolin Hong, Qing Hu, Zhi-Liang Ji, Pan You

“…Abstract Background The escalating mental health crisis during and post-COVID-19 underscores the urgent need for scalable, timely, cost-effective assessment solutions for general psychotic disorders. …”
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A Smartphone-Based Non-Destructive Multimodal Deep Learning Approach Using pH-Sensitive Pitaya Peel Films for Real-Time Fish Freshness Detection by Yixuan Pan, Yujie Wang, Yuzhe Zhou, Jiacheng Zhou, Manxi Chen, Dongling Liu, Feier Li, Can Liu, Mingwan Zeng, Dongjing Jiang, Xiangyang Yuan, Hejun Wu

“…This method eliminates the need for professional equipment and enables real-time, non-destructive detection of fish spoilage through smartphones, providing consumers and the food supply chain with a low-cost, portable quality-monitoring tool, thereby promoting the intelligent and universal development of food safety detection technology.…”
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Early detection of Citrus Huanglongbing by UAV remote sensing based on MGA-UNet by Naibo Ye, Wenyong Mai, Feng Qin, Sen Yuan, Bo Liu, Zaiyuan Li, Conghui Liu, Fanghao Wan, Wanqiang Qian, Zhongzhen Wu, Xi Qiao

“…The intelligent monitoring method for HLB presented in this study offers a cost-effective and highly accurate solution, holding considerable promise for the early warning of this disease.…”
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Estimating and mapping tailings properties of the largest iron cluster in China for resource potential and reuse: A new perspective from interpretable CNN model and proposed spectr... by Haimei Lei, Nisha Bao, Moli Yu, Yue Cao

“…Visible-near infrared-shortwave infrared (VIS-NIR-SWIR; 350–2500 nm) spectroscopy offers a rapid, non-destructive, and cost-effective method for quantitatively analyzing tailings properties. …”
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DM_CorrMatch: a semi-supervised semantic segmentation framework for rapeseed flower coverage estimation using UAV imagery by Jie Li, Chengyong Zhu, Chenbo Yang, Quan Zheng, Binhui Wang, Jingmin Tu, Qian Zhang, Sheng Liu, Xinfa Wang, Jiangwei Qiao

“…In this study, we propose a cost-effective and high-throughput approach using a semi-supervised learning framework, DM_CorrMatch. …”
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Geographic origin discrimination and quantification of phenolic compounds and moisture in Artemisia argyi folium using NIRS and chemometrics by Lifei Hu, Yifan Wang, Xin Wu, Yuanyuan Shan, Fengxiao Zhu, Fan Zhang, Qiang Yang, Mingxing Liu

“…This NIRS-based approach achieved a higher detection efficiency and lower cost compared to conventional methods and thus provides a rapid and efficient solution for the geographic traceability and quantitative evaluation of AAF.…”
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Advanced Hydro-Informatic Modeling Through Feedforward Neural Network, Federated Learning, and Explainable AI for Enhancing Flood Prediction by Shahariar Hossain Mahir, Md Tanjum An Tashrif, Md Ahsan Karim, Dipanjali Kundu, Anichur Rahman, Md. Amir Hamza, Fahmid Al Farid, Abu Saleh Musa Miah, Sarina Mansor

“…Recent advancements in flood prediction research include the development of robust, accurate, and low-cost flood models designed for urban deployment. …”
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A Radiomic-based model to predict the depth of myometrial invasion in endometrial cancer on ultrasound images by Francesca Arezzo, Annarita Fanizzi, Rosanna Mancari, Emiliano Cocco, Samantha Bove, Maria Colomba Comes, Mariangela Gianciotta, Giorgia Lanza, Salvatore Lopez, Gerardo Cazzato, Erica Silvestris, Elsa Vitale, Enrico Vizza, Gennaro Cormio, Raffaella Massafra, Vera Loizzi

“…After a pre-processing phase of ultrasound images, a pre-trained Inception-V3 convolutional neural network (CNN) was used as features extractor. …”
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Early Detection and Classification of Diabetic Retinopathy: A Deep Learning Approach by Mustafa Youldash, Atta Rahman, Manar Alsayed, Abrar Sebiany, Joury Alzayat, Noor Aljishi, Ghaida Alshammari, Mona Alqahtani

“…This not only ensures high-quality patient care but also results in cost savings and contributes to the kingdom’s economic growth, as the traditional process of diagnosing diabetic retinopathy can be both time-consuming and expensive. …”
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Machine learning for the rElapse risk eValuation in acute biliary pancreatitis: The deep learning MINERVA study protocol by Mauro Podda, Adolfo Pisanu, Gianluca Pellino, Adriano De Simone, Lucio Selvaggi, Valentina Murzi, Eleonora Locci, Matteo Rottoli, Giacomo Calini, Stefano Cardelli, Fausto Catena, Carlo Vallicelli, Raffaele Bova, Gabriele Vigutto, Fabrizio D’Acapito, Giorgio Ercolani, Leonardo Solaini, Alan Biloslavo, Paola Germani, Camilla Colutta, Savino Occhionorelli, Domenico Lacavalla, Maria Grazia Sibilla, Stefano Olmi, Matteo Uccelli, Alberto Oldani, Alessio Giordano, Tommaso Guagni, Davina Perini, Francesco Pata, Bruno Nardo, Daniele Paglione, Giusi Franco, Matteo Donadon, Marcello Di Martino, Dario Bruzzese, Daniela Pacella

“…The ML model will utilise convolutional neural networks (CNN) for feature extraction and risk prediction. …”
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Dynamic UAV data fusion and deep learning for improved maize phenological-stage tracking by Ziheng Feng, Jiliang Zhao, Liunan Suo, Heguang Sun, Huiling Long, Hao Yang, Xiaoyu Song, Haikuan Feng, Bo Xu, Guijun Yang, Chunjiang Zhao

“…These methods are not applicable on the unmanned aerial vehicle (UAV) platform due to the high cost of acquiring time–series UAV images and the shortage of UAV–based phenological monitoring methods. …”
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ImageOP: The Image Dataset with Religious Buildings in the World Heritage Town of Ouro Preto for Deep Learning Classification by André Luiz Carvalho Ottoni, Lara Toledo Cordeiro Ottoni

“…MobileNet V2 and EfficientNet B0 are architectures of convolutional neural networks designed for computer vision applications aiming at low computational cost, real-time classification on mobile devices. …”
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Quantum ensemble learning with a programmable superconducting processor by Jiachen Chen, Yaozu Wu, Zhen Yang, Shibo Xu, Xuan Ye, Daili Li, Ke Wang, Chuanyu Zhang, Feitong Jin, Xuhao Zhu, Yu Gao, Ziqi Tan, Zhengyi Cui, Aosai Zhang, Ning Wang, Yiren Zou, Tingting Li, Fanhao Shen, Jiarun Zhong, Zehang Bao, Zitian Zhu, Zixuan Song, Jinfeng Deng, Hang Dong, Pengfei Zhang, Wei Zhang, Hekang Li, Qiujiang Guo, Zhen Wang, Ying Li, Xiaoting Wang, Chao Song, H. Wang

“…However, the vulnerability of quantum information to environmental noises and the consequent high cost for realizing fault tolerance has impeded the quantum models from learning complex datasets. …”
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Morpho-photometric Classification of KiDS DR5 Sources Based on Neural Networks: A Comprehensive Star–Quasar–Galaxy Catalog by Hai-Cheng Feng, Rui Li, Nicola R. Napolitano, Sha-Sha Li, J. M. Bai, Yue Dong, Ran Li, H. T. Liu, Kai-Xing Lu, Zhi-Wei Pan, Mario Radovich, Huan-Yuan Shan, Jian-Guo Wang, Wen-Zhe Xi, Ling-Hua Xie, Zun-Li Yuan, Yang-Wei Zhang

“…Our approach combines a convolutional neural network branch for learning morphological features from r -band images with an artificial neural network branch for extracting spectral energy distribution (SED) information. …”
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A Latent Multi-Scale Residual Transformer Approach for Cross-Modal Medical Image Synthesis by Xinmiao Zhu, Yang Li

“…Consequently, issues arise concerning limited receptive fields and significant increases in computational costs. This paper proposes a latent feature space-based multi-scale residual ViT generative adversarial model (LMRT-NET), which leverages the global sensitivity of ViTs and the local precision of CNNs while reducing computational costs. …”
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MCBA-MVACGAN: A Novel Fault Diagnosis Method for Rotating Machinery Under Small Sample Conditions by Wenhan Huang, Xiangfeng Zhang, Hong Jiang, Zhenfa Shao, Yu Bai

“…In complex industrial scenarios, high-quality fault data of rotating machinery are scarce and costly to collect. Therefore, small sample fault diagnosis needs further research. …”
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BREAST CANCER CAD SYSTEM BY USING TRANSFER LEARNING AND ENHANCED ROI by Muayed S AL-HUSEINY, Ahmed S SAJIT

“… Computer systems are being employed in specialized professions such as medical diagnosis to alleviate some of the costs and to improve dependability and scalability. …”
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A Systematic Review of CNN Architectures, Databases, Performance Metrics, and Applications in Face Recognition by Andisani Nemavhola, Colin Chibaya, Serestina Viriri

“…This study provides a comparative evaluation of face recognition databases and Convolutional Neural Network (CNN) architectures used in training and testing face recognition systems. …”
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MFENet: A Multi-Feature Extraction Network for Enhanced Emotion Detection Using EEG and STFT by N. Ramesh Babu, Viswanathan Vadivel

“…MFENet employs multi-feature extraction blocks and grouped convolutions to enhance representational diversity without incurring high computational costs. …”
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