Enhanced Pollen Classification via Hybrid Neural Network With Attention Mechanism and View Separation: An Equatorial and Polar Approach by Julio Cesar da Silva Soares, Kelson Romulo Teixeira Aires, Juliana do Nascimento Bendini, Wesley Vitor Barbosa Brandao, Rodrigo de Melo Souza Veras

“…Experiments conducted with the Cretan Pollen Dataset, using a hybrid neural network combining of VGG19 and the CBAM attention mechanism, trained from scratch with data augmentation, demonstrated remarkable performance compared to previous studies. …”
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Application of Convolutional Neural Networks for Recognizing Long Structural Elements of Rails in Eddy-Current Defectograms by Egor V. Kuzmin, Oleg E. Gorbunov, Petr O. Plotnikov, Vadim A. Tyukin, Vladimir A. Bashkin

“…Long marks that cannot be assigned to these two classes are conditionally considered as defects and are placed in a separate third class. For image recognition of structural elements in defectograms a convolutional neural network is applied. …”
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Blockchain enabled IoMT and transfer learning for ocular disease classification by Muhammad Adnan Khan, Muhammad Zahid Hussain, Muhammad Farhan Khan, Munir Ahmad, Sagheer Abbas, Tehseen Mazhar, Tariq Shahzad, Mamoon M. Saeed

“…In the proposed work, six different automated convolutional neural network architectures based on the Internet of Medical Things (IoMT) using transfer learning techniques were implemented for the classification of fundus images that can detect ocular diseases. …”
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A NOVEL DEEP LEARNING APPROACHES FOR MULTI-CLASS HISTOPATHOLOGICAL SUB-IMAGE CLASSIFICATION USING PRIOR KNOWLEDGE by Riyam Ali Yassin, Morteza Valizadeh, Alaa Hussein Abdulaal

“…Convolutional neural networks (CNNs) have shown significant promise in medical image analysis, aiding in the detection of cancer cells and the classification of histopathological images through advanced data processing techniques. …”
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Cortical Surface Spatial Analysis Reveals Altered Brain Functional Network Topology in T2DM With Mild Cognitive Impairment by YanJun fan, Jing Tian, XiaoMei Yu, Chen Yang, HuiYan Zhang, Jian Tan, YiWei Zhao, Jing Wei, Gang Huang, JiangPing Liu, LianPing Zhao

“…However, the specific alternations in T2DM with MCI (T2DM‐MCI)‐related brain functional networks (BFN) remain unclear. Therefore, the present study aimed to investigate the alterations in the topological properties of BFN in T2DM patients with and without MCI, utilizing a cortical surface‐based graph theory analysis of resting‐state functional magnetic resonance imaging data. …”
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Reconstructing Evapotranspiration in British Columbia Since 1850 Using Publicly Available Tree-Ring Plots and Climate Data by Hang Li, John Rex

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Smart and accurate: A new tool to identify stressed soybean seeds based on multispectral images and machine learning models by Ana Carolina Picinini Petronilio, Clíssia Barboza Mastrangelo, Thiago Barbosa Batista, Gustavo Roberto Fonseca de Oliveira, Isabela Lopes dos Santos, Edvaldo Aparecido Amaral da Silva

“…We designed machine learning models using multispectral imaging data based on three algorithms: neural network, support vector machine, and random forest. …”
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Machine Learning for the estimation of foliar nitrogen content in pineapple crops using multispectral images and Internet of Things (IoT) platforms by Jorge Enrique Chaparro, José Edinson Aedo, Felipe Lumbreras Ruiz

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Deep-Learning-Based Computer-Aided Grading of Cervical Spinal Stenosis from MR Images: Accuracy and Clinical Alignment by Zhiling Wang, Xinquan Chen, Bin Liu, Jinjin Hai, Kai Qiao, Zhen Yuan, Lianjun Yang, Bin Yan, Zhihai Su, Hai Lu

“…<b>Methods:</b> We retrospectively enrolled 954 patients with cervical spine magnetic resonance imaging (MRI) data and medical records from the Fifth Affiliated Hospital of Sun-Yat Sen University. …”
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Artery segmentation and atherosclerotic plaque quantification using AI for murine whole slide images stained with oil red O by Johann Christopher Engster, Tobias Reinberger, Nele Blum, Pascal Stagge, Thorsten M. Buzug, Zouhair Aherrahrou, Maik Stille

“…Finally, a case study utilizing published mouse data ( $$\text {n}=373$$ slices) underscored the ability of our optimized pipeline to replicate human-made plaque predictions with a high correlation (Pearson’s $$\text {r}=0.91$$ ) and reproduce biological insights derived from manual analysis.…”
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Explainable artificial intelligence with UNet based segmentation and Bayesian machine learning for classification of brain tumors using MRI images by K. Lakshmi, Sibi Amaran, G. Subbulakshmi, S. Padmini, Gyanenedra Prasad Joshi, Woong Cho

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Analysis of Facial Areas to Identify CHD Risks Based on Facial Textures by Budi Sunarko, Agung Adi Firdaus, Yudha Andriano Rismawan, Anan Nugroho

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Graphical representation of landscape heterogeneity identification through unsupervised acoustic analysis by Maria J. Guerrero, Camilo Sánchez‐Giraldo, César A. Uribe, Víctor M. Martínez‐Arias, Claudia Isaza

“…We propose an unsupervised approach using passive acoustic monitoring data and network inference methods to analyse acoustic heterogeneity patterns based on biophony composition. …”
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Integrating Random Forest With Boundary Enhancement for Mapping Crop Planting Structure at the Parcel Level From Remote Sensing Images by Junyang Xie, Yan Li, Hao Wu, Ziwei Wu, Ruina Zhao, Anqi Lin, Marcos Adami, Guoqiang Li, Jian Zhang

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A hybrid learning network with progressive resizing and PCA for diagnosis of cervical cancer on WSI slides by Nitin Kumar Chauhan, Krishna Singh, Amit Kumar, Ashutosh Mishra, Sachin Kumar Gupta, Shubham Mahajan, Seifedine Kadry, Jungeun Kim

“…Deep models that have been pre-trained and tailored through transfer learning and fine-tuning become faster and more effective, even when data is scarce. This paper implements a state-of-the-art Hybrid Learning Network that combines the Progressive Resizing approach and Principal Component Analysis (PCA) for enhanced cervical cancer diagnostics of whole slide images (WSI) slides. …”
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Comparative analysis of object tracking algorithms by B. A. Zalesky, V. A. Ivanyukovich, K. V. Reer, D. A. Starikovich

“…Software tools for gathering and processing experimental data were also implemented.Results. The comparative analysis of three object tracking algorithms allowed us to calculate and compare the characteristics of these trackers, as well as draw conclusions about the method of training the used neural network detector; about the possibility of using trackers in real time on budget personal computers with budget video cards that have the CUDA software and hardware architecture, about the applicability of two of them for solving the problem of practical tracking of drones observed by video cameras with sufficient accuracy and reliability. …”
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Deep learning-based identification of precipitation clouds from all-sky camera data for observatory safety by Mohammad H. Zhoolideh Haghighi, Alireza Ghasrimanesh, Habib Khosroshahi

“…We train our model on a set of roughly 2445 images taken by the INO all-sky camera through the deep learning method based on the EfficientNet network. …”
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Detection of Flexible Pavement Surface Cracks in Coastal Regions Using Deep Learning and 2D/3D Images by Carlos Sanchez, Feng Wang, Yongsheng Bai, Haitao Gong

“…Pavement surface distresses are analyzed by transportation agencies to determine section performance across their pavement networks. To efficiently collect and evaluate thousands of lane-miles, automated processes utilizing image-capturing techniques and detection algorithms are applied to perform these tasks. …”
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An interpretable framework for gastric cancer classification using multi-channel attention mechanisms and transfer learning approach on histopathology images by Muhammad Zubair, Muhammad Owais, Taimur Hassan, Malika Bendechache, Muzammil Hussain, Irfan Hussain, Naoufel Werghi

“…The effectiveness and interchangeability of the three channels are further confirmed by ablation and interchangeability experiments, highlighting the remarkable performance of the framework in GC histopathological image classification tasks. This offers an advanced and pragmatic artificial intelligence solution that addresses challenges posed by unique medical image characteristics for intricate image analysis. …”
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Prediction of Halo Coronal Mass Ejections Using SDO/HMI Vector Magnetic Data Products and a Transformer Model by Hongyang Zhang, Ju Jing, Jason T. L. Wang, Haimin Wang, Yasser Abduallah, Yan Xu, Khalid A. Alobaid, Hameedullah Farooki, Vasyl Yurchyshyn

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