Automatic Segmentation of Dermoscopic Images by Iterative Classification by Maciel Zortea, Stein Olav Skrøvseth, Thomas R. Schopf, Herbert M. Kirchesch, Fred Godtliebsen

“…The seed regions are used as initial training samples, and the lesion segmentation problem is treated as binary classification problem. …”
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Analytical computation for segmentation and classification of lumbar vertebral fractures by Roseline Nyange, Hemachandran Kannan, Channabasava Chola, Saurabh Singh, Jaejeung Kim, Anil Audumbar Pise

“…Subsequently, vertebral are segmented and labeled, with each classified into normal or fractured using classification techniques, k-nearest neighbors (KNN) and support vector machines (SVM). …”
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A Quantum-like Approach to Semantic Text Classification by Anastasia S. Gruzdeva, Rodion N. Iurev, Igor A. Bessmertny, Andrei Y. Khrennikov, Alexander P. Alodjants

“…In this work, we conduct a sentiment analysis of English-language reviews using a quantum-like (wave-based) model of text representation. This model is explored as an alternative to machine learning (ML) techniques for text classification and analysis tasks. …”
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Enhanced Skin Lesion Segmentation and Classification Through Ensemble Models by Su Myat Thwin, Hyun-Seok Park

“…This study addresses challenges in skin cancer detection, particularly issues like class imbalance and the varied appearance of lesions, which complicate segmentation and classification tasks. …”
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SAM2Former: Segment Anything Model 2 Assisting UNet-Like Transformer for Remote Sensing Image Semantic Segmentation by Xuewen Li, Xiaomin Tian, Zihong Wang, Feng Zhang, Yanting Zhang, Na Yang, Chuanzhao Tian

“…Remote sensing semantic segmentation plays a crucial role in the fields of land cover classification, disaster monitoring, and urban planning. …”
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Skin-lesion segmentation using boundary-aware segmentation network and classification based on a mixture of convolutional and transformer neural networks by Javaria Amin, Marium Azhar, Habiba Arshad, Amad Zafar, Seong-Han Kim

“…Therefore, we propose a boundary-aware segmentation network (BASNet) model comprising prediction and residual refinement modules.Materials and methodsThe prediction module works like a U-Net and is densely supervised by an encoder and decoder. …”
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CNN-Based Image Segmentation Approach in Brain Tumor Classification: A Review by Nurul Huda, Ku Ruhana Ku-Mahamud

“…CNN architectures like U-Net, V-Net, and ResNet have shown significant promise in brain tumor classification, offering high precision in detecting tumor boundaries and classifying tumor types. …”
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A novel hybrid vision UNet architecture for brain tumor segmentation and classification by M. Renugadevi, K. Narasimhan, K. Ramkumar, N. Raju

“…Abstract This paper focuses on designing and developing novel architectures termed Hybrid Vision UNet-Encoder Decoder (HVU-ED) segmenter and Hybrid Vision UNet-Encoder (HVU-E) classifier for brain tumor segmentation and classification, respectively. …”
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Adapting Classification Neural Network Architectures for Medical Image Segmentation Using Explainable AI by Arturs Nikulins, Edgars Edelmers, Kaspars Sudars, Inese Polaka

“…A ResNet classification neural network was trained, and XAI tools were applied to generate segmentation-like outputs. …”
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An End-to-End Deep Learning System for Automated Fashion Tagging: Segmentation, Classification, and Hierarchical Labeling by Basak Esin Kokturk-Guzel

“…Following segmentation, the system classifies these items into primary categories, reaching a top-level classification accuracy of 96% with the InceptionV3 model, and determines their dominant color with an RGB-based color-matching algorithm. …”
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Multi-task advanced convolutional neural network for robust lymphoblastic leukemia diagnosis, classification, and segmentation by Sercan Yalcin, Zuhal Cetin Yalcin, Muhammed Yildirim, Bilal Alatas

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A comprehensive reservoir segmentation for hydrodynamics and water quality assessment by Camila Bergmann Goulart, João Marcos Carvalho, Julio Werner Yoshioka Bernardo, Bruna Arcie Polli, Cristóvão Fernandes, Stephan Fuchs, Tobias Bleninger

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Enhanced electrocardiogram classification using Gramian angular field transformation with multi-lead analysis and segmentation techniques by Gi-Won Yoon, Segyeong Joo

“…F1-score for AFib, LVH, RVH and Normal ECG were 0.781, 0.71, 0.521 and 0.792 respectively. Segmentation methods improved classification performance, especially in detecting conditions like LVH and RVH. …”
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Classification and lateralization of temporal lobe epilepsies with and without hippocampal atrophy based on whole-brain automatic MRI segmentation. by Shiva Keihaninejad, Rolf A Heckemann, Ioannis S Gousias, Joseph V Hajnal, John S Duncan, Paul Aljabar, Daniel Rueckert, Alexander Hammers

“…Such morphometric image features may serve as classification and lateralization criteria. The technique also detects unsuspected distinguishing features like the substantia nigra, warranting further study.…”
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Edge Computing for AI-Based Brain MRI Applications: A Critical Evaluation of Real-Time Classification and Segmentation by Khuhed Memon, Norashikin Yahya, Mohd Zuki Yusoff, Rabani Remli, Aida-Widure Mustapha Mohd Mustapha, Hilwati Hashim, Syed Saad Azhar Ali, Shahabuddin Siddiqui

“…In this research, the capabilities of multiple platforms are evaluated for the real-time deployment of diagnostic tools. MRI classification and segmentation applications developed in previous studies are used for testing the performance using different hardware and software configurations. …”
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Deep dive into deep learning methods for cervical cancer detection and classification by Pooja Patre, Dipti Verma

“…We explore various deep learning architectures, particularly convolutional neural networks (CNNs), and their applications in the segmentation and classification of cervical cytology images. …”
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An anatomically enhanced and clinically validated framework for lung abnormality classification using deep features and KL divergence by Suresh Kumar Samarla, Maragathavalli P

“…This approach integrates segmentation and tissue-specific color enhancements with Kullback-Leibler (KL) divergence, quantifying deviations from healthy lung regions for improved classification. …”
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DRSegNet: A cutting-edge approach to Diabetic Retinopathy segmentation and classification using parameter-aware Nature-Inspired optimization. by Sundreen Asad Kamal, Youtian Du, Majdi Khalid, Majed Farrash, Sahraoui Dhelim

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Smart neural network and cognitive computing process for multi task nuclei detection segmentation and classification in breast cancer histopathology images by M. Suriya Begum, S. Kalaivani

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ASLDetect: Arabic sign language detection using ResNet and U-Net like component by Naif Alasmari, Sultan Asiri

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