Optimizing Defect Detection on Glossy and Curved Surfaces Using Deep Learning and Advanced Imaging Systems by Joung-Hwan Yoon, Chibuzo Nwabufo Okwuosa, Nnamdi Chukwunweike Aronwora, Jang-Wook Hur

“…Consequently, this study presents an enhanced method for curvy and glossy surface image data collection using a Basler vision camera with specialized lighting and KEYENCE displacement sensors, which are used to train deep learning models. …”
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Multi-Scale Venation Pattern Analysis for Medicinal Plant Species Recognition by Arnav Sanjay Karnik, Nikhil Nair, Yashas Sagili, P. B. Pb

“…We propose a novel, venation-aware methodology that combines specialized image preprocessing techniques with both transfer learning and custom-designed deep learning architectures. …”
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Multi-scale window transformer for cervical cytopathology image recognition by Jiaxiang Yi, Xiuli Liu, Shenghua Cheng, Li Chen, Shaoqun Zeng

“…Extensive experiments demonstrate that our MWT outperforms state-of-the-art general classification networks and specialized classifiers for cytopathology images in the internal and external test sets. …”
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Efficient and Motion Correction-Free Myocardial Perfusion Segmentation in Small MRI Data Using Deep Transfer Learning From Cine Images: A Promising Framework for Clinical Implement... by German Garcia-Jara, Angel Jimenez-Molina, Esteban Reyes, Nicolas Tapia-Rivas, Cristobal Ramos-Gomez, Jose De Grazia, Matias Sepulveda

“…After pretraining a U-net convolutional neural network, a special fine-tuning scheme optimizes its performance. …”
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Apple Watercore Grade Classification Method Based on ConvNeXt and Visible/Near-Infrared Spectroscopy by Chunlin Zhao, Zhipeng Yin, Yushuo Tan, Wenbin Zhang, Panpan Guo, Yaxing Ma, Haijian Wu, Ding Hu, Quan Lu

“…The apples were then sliced into 4.5 mm thick sections using a specialized tool, and image data of each slice were captured. …”
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CapsuleThermNet: A CNN-CapsuleNet Architecture for Early Detection of Suicide Risk in Depressed Patients Using Thermal Facial Imaging by Eddy Muntina Dharma, Harjanto Prabowo, Agung Trisetyarso, Tjhin Wiguna

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Recent Advances in Fault Diagnosis Methods for Electrical Motors- A Comprehensive Review with Emphasis on Deep Learning by Jawad Faiz, F. Parvin

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Ai-powered digital twin in the industrial IoT by Željko Bolbotinović, Saša D. Milić, Žarko Janda, Dragan Vukmirović

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A Deep Learning Based Analysis of the Big Five Personality Traits from Handwriting Samples Using Image Processing by Ahmed Elngar, Nikita Jain, Divyanshu Sharma, Himani Negi, Anuj Trehan, Akash Srivastava

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An End-to-End Concatenated CNN Attention Model for the Classification of Lung Cancer With XAI Techniques by Fariha Haque, Mohammad Asif Hasan, Md. Abu Ismail Siddique, Tonmoy Roy, Tonmoy Kanti Shaha, Yamina Islam, Avijit Paul, Muhammad E. H. Chowdhury

“…However, manual diagnosis is labor-intensive, requiring the specialized expertise of radiologists, and the increasing number of cancer cases presents challenges in processing large volumes of image data efficiently. …”
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Multi-Branch CNN-LSTM Fusion Network-Driven System With BERT Semantic Evaluator for Radiology Reporting in Emergency Head CTs by Selene Tomassini, Damiano Duranti, Abdallah Zeggada, Carlo Cosimo Quattrocchi, Farid Melgani, Paolo Giorgini

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LCC-Net: Swin transformer-CNN hybrid for enhanced land cover classification in natural disaster monitoring by P. Shailaja, Pala Mahesh Kumar, Nalla Nikhitha, Kunta Neeraj Kumar Reddy, Enthala Mukesh Reddy, Goli Ganesh Reddy, Vadde Indu

“…This research proposes a specialized network named the land cover classification network, referred to as LCC-Net, for classifying the land covers from satellite images. …”
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Dual-Branch Deep Learning with Dynamic Stage Detection for CT Tube Life Prediction by Zhu Chen, Yuedan Liu, Zhibin Qin, Haojie Li, Siyuan Xie, Litian Fan, Qilin Liu, Jin Huang

“…This architecture consists of two specialized branches: a residual self-attention BiLSTM (RSA-BiLSTM) and a multi-layer dilation temporal convolutional network (D-TCN). …”
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A Novel Tactile Learning Assistive Tool for the Visually and Hearing Impaired with 3D-CNN and Bidirectional LSTM Leveraging Morse Code Technology by Shabana Ziyad Puthu Vedu, May Altulyan, Pradeep Kumar Singh

“…Educating deafblind children is a highly specialized field that requires computer-assisted learning tools to address the challenges of auditory and visual impairments. …”
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gamUnet: designing global attention-based CNN architectures for enhanced oral cancer detection and segmentation by Jinyang Zhang, Hongxin Ding, Hongxin Ding, Runchuan Zhu, Weibin Liao, Weibin Liao, Junfeng Zhao, Junfeng Zhao, Min Gao, Xiaoyun Zhang

“…Conventional diagnosis relies on manual evaluation of hematoxylin and eosin (H&E)-stained slides, a time-consuming process requiring specialized expertise and prone to variability. While deep learning methods, especially convolutional neural networks (CNNs), have advanced automated analysis of histopathological images for cancerous tissues in various body parts, OSCC presents unique challenges. …”
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Advancing e-waste classification with customizable YOLO based deep learning models by P. Akhil Rajeev, Vivek Dharewa, D. Lakshmi, G. Vishnuvarthanan, Jayant Giri, T. Sathish, Mubarak Alrashoud

“…This research approach involved the creation of a specialized image dataset encompassing seven distinct e-waste categories to facilitate the training and validation of these models. …”
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Deep learning approach for automated hMPV classification by Sivarama Prasad Tera, Ravikumar Chinthaginjala, Irum Shahzadi, Priya Natha, Safia Obaidur Rab

“…This study proposes a novel deep learning framework, referred to as hMPV-Net, which leverages Convolutional Neural Networks (CNNs) to facilitate the precise detection and classification of hMPV infections. …”
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Review of Synthetic Aperture Radar Automatic Target Recognition: A Dual Perspective on Classical and Deep Learning Techniques by Jakub Slesinski, Damian Wierzbicki

“…What makes SAR imagery particularly unique are problems, such as speckle noise, target variability, and clutter, for which there are specialized solutions described in this article. Feature-based approaches in traditional SAR ATR followed from conventional feature-driven strategies, while modern data-driven end-to-end recognition methods, consisting primarily of convolutional neural network based and hybrid networks, have been applied. …”
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Adjusting Xception Neural Network by Improved Human Evolutionary Optimizer for Fine Art Sorting by Tianfu Liu

“…The model architecture of the Xception model, which uses a depth-wise separable convolution, allowing for a better capture of complex features, and introduced specialized IHEO, to enhance the task performance on fine art classification tasks. …”
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Automatic Number Plate Detection and Recognition System for Small-Sized Number Plates of Category L-Vehicles for Remote Emission Sensing Applications by Hafiz Hashim Imtiaz, Paul Schaffer, Paul Hesse, Martin Kupper, Alexander Bergmann

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