Enhancing the accuracy and generalizability of reference evapotranspiration forecasting in California using deep global learning by Arman Ahmadi, Andre Daccache, Minxue He, Peyman Namadi, Alireza Ghaderi Bafti, Prabhjot Sandhu, Zhaojun Bai, Richard L. Snyder, Tariq Kadir

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Dysfluent Speech Classification Using Variational Mode Decomposition and Complete Ensemble Empirical Mode Decomposition Techniques With NGCU-Based RNN by N. A. Vinay, K. N. Vidyasagar, S. Rohith, S. Supreeth, S. N. Prasad, S. Pramod Kumar, S. H. Bharathi

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A Multi-Year Investigation of Thunderstorm Activity at Istanbul International Airport Using Atmospheric Stability Indices by Oğuzhan Kolay, Bahtiyar Efe, Emrah Tuncay Özdemir, Zafer Aslan

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Multi-Pathway 3D CNN With Conditional Random Field for Automated Segmentation of Multiple Sclerosis Lesions in MRI by Reeda Saeed, Shahab U. Ansari, Muhammad Hanif, Kamran Javed, Usman Haider, Iffat Maab, Saeed Mian Qaisar, Pawel Plawiak

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Focal liver lesion diagnosis with deep learning and multistage CT imaging by Yi Wei, Meiyi Yang, Meng Zhang, Feifei Gao, Ning Zhang, Fubi Hu, Xiao Zhang, Shasha Zhang, Zixing Huang, Lifeng Xu, Feng Zhang, Minghui Liu, Jiali Deng, Xuan Cheng, Tianshu Xie, Xiaomin Wang, Nianbo Liu, Haigang Gong, Shaocheng Zhu, Bin Song, Ming Liu

“…This study develops an automatic diagnosis system for liver lesions using multiphase enhanced computed tomography (CT). …”
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Alzheimer’s Disease Detection Using Deep Learning and Federated Learning by Taha Bin Niaz, Usman Amjad, Humera

“… Appropriate and precise diagnosis of brain diseases is crucial as many forms of Alzheimer’s disease display similar indications in their initial stages. Most automatic detection or classification systems based on deep learning present confidentiality concerns due to their use of integrated computing and local storage data requirements for training. …”
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Lightweight patch-level attention for efficient pig behavior detection: A novel dataset and approach by Shuo Wan, Zhongqiang Huang, Tao Han, Ying Sha

“…Pig behavior detection involves the automatic recognition and classification of pig behaviors in farm images using computer vision and deep learning techniques. …”
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An adaptive search mechanism with convolutional learning networks for online social media text summarization and classification model by Reema G. AL-anazi, Muhammad Swaileh A. Alzaidi, Majdy M. Eltahir, Hassan Alkhiri, Samah Hazzaa Alajmani, Abdulbasit A. Darem, Mohammed Alshahrani, Nawaf Alhebaishi

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An Improved Size and Direction Adaptive Filtering Method for Bathymetry Using ATLAS ATL03 Data by Lei Kuang, Mingquan Liu, Dongfang Zhang, Chengjun Li, Lihe Wu

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MEMS and IoT in HAR: Effective Monitoring for the Health of Older People by Luigi Bibbò, Giovanni Angiulli, Filippo Laganà, Danilo Pratticò, Francesco Cotroneo, Fabio La Foresta, Mario Versaci

“…In this context, this article presents an IoT application based on MEMS (micro electro-mechanical systems) sensors integrated into a state-of-the-art microcontroller (STM55WB) for recognizing the movements of older individuals during daily activities. human activity recognition (HAR) is a field within computational engineering that focuses on automatically classifying human actions through data captured by sensors. …”
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The Potential for High-Priority Care Based on Pain Through Facial Expression Detection with Patients Experiencing Chest Pain by Hsiang Kao, Rita Wiryasaputra, Yo-Yun Liao, Yu-Tse Tsan, Wei-Min Chu, Yi-Hsuan Chen, Tzu-Chieh Lin, Chao-Tung Yang

“…Moreover, a limited number of emergency care (ER) medical personnel serve unscheduled outpatients. In this study, a computer-based automatic chest pain detection assistance system is developed using facial expressions to improve patient care services and minimize heart damage. …”
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UnionCAM: enhancing CNN interpretability through denoising, weighted fusion, and selective high-quality class activation mapping by Hao Hu, Hao Hu, Rui Wang, Hao Lin, Huai Yu

“…UnionCAM makes notable contributions by introducing a novel denoising strategy, adaptive fusion of CAMs, and an automatic selection mechanism. It bridges the gap between CNN performance and interpretability, providing a valuable tool for understanding and trusting CNN-based systems. …”
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GastroEndoNet: Comprehensive endoscopy image dataset for GERD and polyp detectionMendeley Data by Abu Kowshir Bitto, Md. Hasan Imam Bijoy, Kamrul Hassan Shakil, Aka Das, Khalid Been Badruzzaman Biplob, Imran Mahmud, Syed Md. Minhaz Hossain

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Disturbance Observer-Based Adaptive Current Control With Self-Learning Ability to Improve the Grid-Injected Current for <inline-formula> <tex-math notation="LaTeX">$LCL$ </tex-math... by Jiahao Liu, Weimin Wu, Henry Shu-Hung Chung, Frede Blaabjerg

“…The control parameters can be automatically adjusted in real time by adaptive learning rule, which significantly improves the system robustness and the control performance. …”
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An Ensemble Hybrid Framework: A Comparative Analysis of Metaheuristic Algorithms for Ensemble Hybrid CNN Features for Plants Disease Classification by Khaoula Taji, Ali Sohail, Tariq Shahzad, Bilal Shoaib Khan, Muhammad Adnan Khan, Khmaies Ouahada

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Lifelong Learning-Enabled Fractional Order-Convolutional Encoder Model for Open-Circuit Fault Diagnosis of Power Converters Under Multi-Conditions by Tao Li, Enyu Wang, Jun Yang

“…Open-circuit (OC) faults in power converters are common issues in motor drive systems, significantly affecting the safe and stable operation of the system. …”
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Robust Classification of Intramuscular EMG Signals to Aid the Diagnosis of Neuromuscular Disorders by Shobha Jose, S. Thomas George, M. S. P. Subathra, Vikram Shenoy Handiru, Poornaselvan Kittu Jeevanandam, Umberto Amato, Easter Selvan Suviseshamuthu

“…<italic>Goal:</italic> This article presents the design and validation of an accurate automatic diagnostic system to classify intramuscular EMG (iEMG) signals into healthy, myopathy, or neuropathy categories to aid the diagnosis of neuromuscular diseases. …”
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Increased Brain Iron Deposition in the Putamen in Patients with Type 2 Diabetes Mellitus Detected by Quantitative Susceptibility Mapping by Jing Li, Qihao Zhang, Nan Zhang, Lingfei Guo

“…Brain QSM maps were computed from multiecho GRE data using morphology-enabled dipole inversion with automatic uniform cerebrospinal fluid zero reference algorithm (MEDI+0). …”
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Alpine pasture herbs redirected hydrogen towards alternative sinks, inhibiting methane production: in vitro study by Selene Massaro, Nicolò Amalfitano, Jonas Bylov Hedegaard Andersen, Giulia Dallavalle, Andrea Angeli, Nebojša Nikolić, Lucia Bailoni, Sarah Currò, Urska Vrhovsek, Elena Franciosi, Franco Tagliapietra

“…The seven plants were fermented using an automatic in vitro system to evaluate the kinetics of gas production (GP), degraded dry matter (dDM) and fermentation end products [volatile fatty acids (VFA), carbon dioxide, methane, and hydrogen]. …”
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Multi-Scale Crack Detection and Quantification of Concrete Bridges Based on Aerial Photography and Improved Object Detection Network by Liming Zhou, Haowen Jia, Shang Jiang, Fei Xu, Hao Tang, Chao Xiang, Guoqing Wang, Hemin Zheng, Lingkun Chen

“…The key contributions of this method are as follows: (1) The DCN-BiFPN-EMA-YOLO (DBE-YOLO) crack detection network is introduced, which improves the model’s ability to extract crack features from complex backgrounds and enhances its multi-scale detection capability for accurate detection; (2) a more comprehensive crack quantification method is proposed, integrating the crack automation detection system for accurate crack quantification and efficient processing; (3) crack information is mapped onto the 3D model by computing the camera pose for each image in the 3D model for intuitive crack visualization. …”
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