A data mining technique for detecting malignant mesothelioma cancer using multiple regression analysis by Alali Abdulla Mousa Falah, Padmaja Dhyaram Lakshmi, Soni Mukesh, Khan Muhammad Attique, Khan Faheem, Ofori Isaac

“…Classification algorithms for MM illness diagnosis were carried out using computationally efficient data mining techniques. The support vector machine outperformed the multilayer perceptron ensembles (MLPE) neural network (NN) technique, yielding promising findings. …”
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Weak Edge Detection Algorithm for Medical Images Based on Full Convolution Neural Network by LI Xiao-feng, LI Dong, WANG Yan-wei

“…Aiming at the existing image weak edge detection algorithm，it is easy to ignore the selection of threshold in edge calculation，and there is no clustering analysis of the data，which leads to the problem that the detection effect is not good. …”
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Comparative exploration of deep convolutional neural networks using real-time endoscopy images by Subhashree Mohapatra, Pukhraj Singh Jeji, Girish Kumar Pati, Manohar Mishra, Tripti Swarnkar

“…Once the data annotation is completed, the images are segregated into the class of normal and abnormal endoscopy images. …”
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Integrating convolutional neural networks for microscopic image analysis in acute lymphoblastic leukemia classification: A deep learning approach for enhanced diagnostic precision by Md. Samiul Alim, Suborno Deb Bappon, Shahriar Mahmud Sabuj, Md Jayedul Islam, M. Masud Tarek, Md. Shafiul Azam, Md. Monirul Islam

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Artificial intelligence-assisted diagnosis of early allograft dysfunction based on ultrasound image and data by Yaqing Meng, Mingyang Wang, Ningning Niu, Haoyan Zhang, Jinghan Yang, Guoying Zhang, Jing Liu, Ying Tang, Kun Wang

“…The AUC for the ultrasound-spectrogram fusion network constructed from four ultrasound images and medical data was 0.968 (95%CI: 0.940, 0.991), outperforming radiologists by 30% for all metrics. …”
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EFFC-Net: lightweight fully convolutional neural networks in remote sensing disaster images by Jianye Yuan, Xin Ma, Zhentong Zhang, Qiang Xu, Ge Han, Song Li, Wei Gong, Fangyuan Liu, Xin Cai

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Detection and classification of breast cancer in mammographic images with fine-tuned convolutional neural networks by Huong Hoang Luong, Hai Thanh Nguyen, Nguyen Thai-Nghe

“…This study proposed a procedure to fine-tune the Convolutional Neural Networks (CNN) model with data preprocessing and augmentation in classifying mammogram images called the Hybrid Mammogram Classification and Detection Pipeline (HMCaD). …”
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Multi-Task Faces (MTF) Data Set: A Legally and Ethically Compliant Collection of Face Images for Various Classification Tasks by Rami Haffar, David Sanchez, Josep Domingo-Ferrer

“…However, recent privacy regulations, particularly the EU General Data Protection Regulation, have restricted the collection and usage of human images in research. …”
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Leveraging machine learning techniques for image classification and revealing social media insights into human engagement with urban wild spaces by Haider Khalid, Marcus J. Collier

“…Abstract In recent years, machine learning models have exhibited excellent performance and far-reaching impact across domains such as fraud detection in finance, recommendation systems in e-commerce, medical imaging in healthcare, agricultural forecasting, social engagement, image classification, sentiment analysis in social media network analysis. …”
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Dual Fine-Grained network with frequency Transformer for change detection on remote sensing images by Zhen Li, Zhenxin Zhang, Mengmeng Li, Liqiang Zhang, Xueli Peng, Rixing He, Leidong Shi

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Enhancing Dermatological Diagnosis Through Medical Image Analysis: How Effective Is YOLO11 Compared to Leading CNN Models? by Rakib Ahammed Diptho, Sarnali Basak

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Enhancing Remote Sensing Image Quality through Data Fusion and Synthetic Aperture Radar (SAR): A Comparative Analysis of CNN, Lightweight ConvNet, and VGG16 Models by Desynike Puspa Anggreyni, Indriatmoko, Aniati Murni Arymurthy, Andie Setiyoko

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Longitudinal whole-brain analysis of multi-subject diffusion data in diffuse axonal injury by Daphine Centola Grassi, Ana Luiza Zaninotto, Fabrício Stewan Feltrin, Fabíola Bezerra de Carvalho Macruz, Maria Concepción García Otaduy, Claudia da Costa Leite, Vinicius Monteiro de Paula Guirado, Wellingson Silva Paiva, Celi Santos Andrade

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Adaptive convolutional neural network-based principal component analysis algorithm for the detection of manufacturing data by Tsun-Kuo Lin

“…Herein, an adaptive convolutional neural network (CNN)-based principal component analysis (PCA) algorithm for the detection of manufacturing data is proposed. …”
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Resilient execution of distributed X-ray image analysis workflows by Hai Duc Nguyen, Tekin Bicer, Bogdan Nicolae, Rajkumar Kettimuthu, E. A. Huerta, E. A. Huerta, Ian T. Foster, Ian T. Foster

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EDB-Net: Efficient Dual-Branch Convolutional Transformer Network for Hyperspectral Image Classification by Hufeng Guo, Wenyi Liu

“…Hyperspectral image (HSI) classification, as a pivotal technology in remote sensing data processing, has garnered significant attention in recent years. …”
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Role of artificial intelligence in medical radiology and imaging by Mohd Arfat, T. K. Nisha, Sapna Sahu, Mohd Rashid

“…Radiologists face challenges, particularly the overwhelming volume of imaging data, which AI helps manage through artificial neural networks and machine learning (ML) algorithms—two significant innovations in this field. …”
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Time Series Classification Using Federated Convolutional Neural Networks and Image-Based Representations by Felipe A. R. Silva, Omid Orang, Fabricio Javier Erazo-Costa, Petronio C. L. Silva, Pedro H. Barros, Ricardo P. M. Ferreira, Frederico Gadelha Guimaraes

“…This research introduces a federated hybrid TSC method that combines image-based time series representation techniques with Convolutional Neural Networks (CNNs) in a decentralized framework. …”
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A Multihierarchy Flow Field Prediction Network for Multimodal Remote Sensing Image Registration by Wenqing Wang, Kunpeng Mu, Han Liu

“…At the same time, the photometric error loss is introduced to optimize the entire network from both the feature and original image levels. …”
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PlantNet: Scalable Convolutional Neural Network for Image-Based Plant Disease Detection by Sinha Anupa, Kumaraswamy Balasubramaniam

“…This research presents PlantNet, a novel Convolutional Neural Network (CNN) architecture tailored for accurate identification of plant diseases from images. …”
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