Predicting and Mitigating Delays in Cross-Dock Operations: A Data-Driven Approach by Amna Altaf, Adeel Mehmood, Adnen El Amraoui, François Delmotte, Christophe Lecoutre

“…This paper investigates the effectiveness of deep learning models, including Convolutional Neural Networks (CNN), Multilayer Perceptrons (MLPs), and Recurrent Neural Networks (RNNs), in predicting late arrivals of trucks. …”
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EM-COGLOAD: An investigation into age and cognitive load detection using eye tracking and deep learning by Gabriella Miles, Melvyn Smith, Nancy Zook, Wenhao Zhang

“…Alzheimer’s Disease is the most prevalent neurodegenerative disease, and is a leading cause of disability among the elderly. …”
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A Spectral Interpretable Bearing Fault Diagnosis Framework Powered by Large Language Models by Panfeng Bao, Wenjun Yi, Yue Zhu, Yufeng Shen, Haotian Peng

“…A channel attention-augmented convolutional neural network provides an initial fault type prediction. …”
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Evaluation of Deep Learning Models for Polymetallic Nodule Detection and Segmentation in Seafloor Imagery by Gabriel Loureiro, André Dias, José Almeida, Alfredo Martins, Eduardo Silva

“…Traditional deep learning methods are based on the use of convolutional layers to extract features, while recent architectures, such as transformer-based architectures, use self-attention mechanisms to obtain global context. …”
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Retraining and evaluation of machine learning and deep learning models for seizure classification from EEG data by Juan Pablo Carvajal-Dossman¹, Laura Guio, Danilo García-Orjuela, Jennifer J. Guzmán-Porras, Kelly Garces, Andres Naranjo, Silvia Juliana Maradei-Anaya, Jorge Duitama

“…Abstract Electroencephalography (EEG) is one of the most used techniques to perform diagnosis of epilepsy. …”
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Exploration of genetic algorithms to build a balanced neutron spectra dataset useful to train unfolding techniques based on artificial neural networks by Bouhadida Maha, Hmede Rodayna, Brovchenko Mariya, Monange Wilfried, Vinchon Thibaut, Ducasse Quentin, Trompier François

“…The resulting dataset is then used to train a new convolutional neural network architecture for unfolding neutron spectra. …”
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Medical Image Hybrid Watermark Algorithm Based on Frequency Domain Processing and Inception v3 by Yu Fan, Jingbing Li, Uzair Aslam Bhatti, Saqib Ali Nawaz, Yenwei Chen

“…Existing research has mostly focused on optimizing individual techniques, lacking comprehensive solutions that integrate the strengths of different methods. …”
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Gait Recognition With Wearable Sensors Using Modified Residual Block-Based Lightweight CNN by Md. Al Mehedi Hasan, Fuad Al Abir, Md. Al Siam, Jungpil Shin

“…We have modified the residual block and accumulated it in shallow convolutional neural networks with five weighted layers only for gait recognition and proved the efficacy of all the architectural components with extensive experiments over publicly available IMU-based datasets: whuGait and OU-ISIR. …”
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Research on Open-Set Recognition Methods for Rolling Bearing Fault Diagnosis by Jia Xu, Yan Wang, Renyi Xu, Hailin Wang, Xinzhi Zhou

“…The framework is built upon a serial multi-scale convolutional prototype learning (SMCPL) network, enhanced with an efficient channel attention (ECA) mechanism to extract the most critical fault features. …”
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Systematic Review on Automation of Central Tire Inflation System Based on Terrain Conditions by Carl Luis C. Ledesma, Charlothe John I. Tablizo, Marites B. Tabanao, Emmanuel A. Salcedo, Emmy Grace T. Requillo, John Paul T. Cruz

“…This study aims to integrate the terrain recognition component using a convolutional neural network (CNN) by reviewing previous terrain-detection models. …”
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Automatic Classification of Red Blood Cell Morphology Based on Quantitative Phase Imaging by Mengduo Jiang, Meng Shao, Xiao Yang, Linna He, Tao Peng, Tao Wang, Zeyu Ke, Zixin Wang, Shu Fang, Yuxin Mao, Xilin Ouyang, Gang Zhao, Jinhua Zhou

“…Compared with the traditional convolutional neural network, the developed method showed a lower misclassification rate and less processing time, especially for RBCs with more discocytes. …”
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A Novel Skin Cancer Detection Approach Using Deep Learning Algorithm with Image Segmentation Filters by Awf A. Ramadhan, Omer S. Kareem, Diyar Q. Zeebaree

“… Skin cancer is considered one of the most common and dangerous diseases in the world because so many people do not pay attention to it. …”
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Evaluation Model Based on the SGCNiFormer for the Influence of Different Storage Environments on Wheat Quality by Qingchuan Zhang, Zexi Song, Mingwen Bi

“…The system incorporates a graph convolutional network (GCN) and a dynamic gating module, enabling precise simulation of the multidimensional evolution of wheat quality under the interaction of moisture and temperature. …”
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DMA‐Net: A dual branch encoder and multi‐scale cross attention fusion network for skin lesion segmentation by Guangyao Zhai, Guanglei Wang, Qinghua Shang, Yan Li, Hongrui Wang

“…The dice similarity coefficient scores on the three datasets reached 81.77%, 81.68% and 85.60%, respectively, surpassing most state‐of‐the‐art methods.…”
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Micro-expression spotting based on multi-modal hierarchical semantic guided deep fusion and optical flow driven feature integration by Haolin Chang, Zhihua Xie, Fan Yang

“…To address this issue, this paper proposes a multi-scale hierarchical semantic-guided end-to-end multimodal fusion framework based on Convolutional Neural Network (CNN)-Transformer for MES, named MESFusion. …”
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Performance Evaluation of Hybrid Bio-Inspired and Deep Learning Algorithms in Gene Selection and Cancer Classification by Shahad S. Alkamli, Hala M. Alshamlan

“…Conversely, deep learning models, including convolutional neural networks and autoencoders, demonstrate superior feature extraction but often require larger datasets and higher computational resources. …”
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Maturity Classification and Quality Determination of Cherry Using VNIR Hyperspectral Images and Comprehensive Chemometrics by Yuzhen Wei, Siyi Yao, Feiyue Wu, Qiangguo Yu

“…Sweetness and acidity are the two most important indicators to evaluate cherry quality. …”
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Advancements in Hematologic Malignancy Detection: A Comprehensive Survey of Methodologies and Emerging Trends by Rajashree Nambiar, Ranjith Bhat, Balachandra Achar H V

“…This survey systematically examines the state-of-the-art in blood cancer detection through image-based analysis, aimed at identifying the most effective computational strategies and highlighting emerging trends. …”
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Deep learning-based occlusion-aware face mask detection for airborne disease control by Teshome Ayechiluhem Yalew, Sosina M. Gashaw, Aleka Melese Ayalew, Mourad Oussalah

“…A dataset of 4,820 images, including occlusions from hands, objects, and mask misuse, was used to train and evaluate three convolutional neural network models: InceptionV3, MobileNetV2, and DenseNet121. …”
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MixtureRS: A Mixture of Expert Network Based Remote Sensing Land Classification by Yimei Liu, Changyuan Wu, Minglei Guan, Jingzhe Wang

“…Our approach employs a 3-D plus heterogeneous convolutional stack to extract rich spectral–spatial features, which are then tokenized and fused via a cross-modality transformer. …”
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