Analysis of breast cancer classification and segmentation techniques: A comprehensive review by Malaya Kumar Nath, Kohilavani Sundararajan, Shanmathi Mathivanan, Bhagyashree Thandapani

“…This study identifies ongoing issues essential for driving future advancements in BC detection and segmentation to improve clinical outcomes.…”
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Computer-Aided Diagnosis Techniques for Brain Tumor Segmentation and Classification Using MRI by Gadicha A. B., Kale Prachi V., Dalvi G. D., Mohod M. M., Pakhale S. C., Khan S. M.

“…In response, artificial intelligence (AI)-based methods, particularly those employing machine learning and deep learning, have shown significant potential in enhancing the accuracy and efficiency of tumor segmentation and classification. This paper presents a comprehensive review of various AI-driven techniques, including traditional ML models, deep convolutional neural networks, and hybrid systems, that have been employed for the automatic detection, segmentation, and categorization of brain tumors using MRI data. …”
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VSA-GCNN: Attention Guided Graph Neural Networks for Brain Tumor Segmentation and Classification by Kambham Pratap Joshi, Vishruth Boraiah Gowda, Parameshachari Bidare Divakarachari, Paramesh Siddappa Parameshwarappa, Raj Kumar Patra

“…From the overall observation, the proposed VSA-GCNN-BiGRU supports accurate brain tumor segmentation and classification, which provides clinical significance in MRI when compared to existing models.…”
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Construction and validation of a deep learning-based diagnostic model for segmentation and classification of diabetic foot by Guang-Xin Zhou, Yu-Kun Tao, Jin-Zheng Hou, Hui-Juan Zhu, Li Xiao, Na Zhao, Xiao-Wen Wang, Bao-Lin Du, Da Zhang

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Brain Tumour Segmentation and Grading Using Local and Global Context-Aggregated Attention Network Architecture by Ahmed Abdulhakim Al-Absi, Rui Fu, Nadhem Ebrahim, Mohammed Abdulhakim Al-Absi, Dae-Ki Kang

“…Segmentation refers to the identification and delineation of tumour regions in medical images, while classification classifies based on tumour characteristics, such as the size, location and enhancement pattern. …”
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Building type classification using deep learning for transport planning by Aniruddha Khatua, Arkopal K. Goswami, Bharath H. Aithal

“…The classification challenge is accomplished through instance segmentation using the state-of-the-art YOLOV8 model architecture and remotely sensed images. …”
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Standard Classes for Urban Topographic Mapping with ALS: Classification Scheme and a First Implementation by Agata Walicka, Norbert Pfeifer

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Application of Object Based Image Classification Using Orthophotos: A Case Study of the Van-Erciş Earthquake by Aslı Sabuncu, Filiz Sunar

“…As an initial step, segmentation process was carried out by selecting the most suitable parameters for the classification of both homogenous and heterogeneous areas. …”
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Glaucoma identification with retinal fundus images using deep learning: Systematic review by Dulani Meedeniya, Thisara Shyamalee, Gilbert Lim, Pratheepan Yogarajah

“…Compared to existing survey studies, we cover the latest research, including several public retinal fundus image datasets, and focus on segmentation, classification based on convolutional neural networks and vision transformers, and explainability. …”
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HiGMA-DADCN: Hirudinaria granulosa multitropic algorithm optimised double attention enabled deep convolutional neural network for psoriasis classification by Soumya C S, Jayanna H S

“…Its visible symptoms such as red, dry patches and persistent itchiness can severely affect a person’s quality of life. Although many researchers have worked on psoriasis classification, existing methods often fall short. …”
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Review and practical excursus on the comparison between traditional statics methods and Classification And Regression Tree (CART) in real-life data: Low protein diet compared to Me... by Vincenzo Calabrese, Daniela Metro, Angela Alibrandi, Domenico Maviglia, Valeria Cernaro, Veronica Maressa, Elisa Longhitano, Guido Gembillo, Domenico Santoro

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Systematic Review: AI Applications in Liver Imaging with a Focus on Segmentation and Detection by Mihai Dan Pomohaci, Mugur Cristian Grasu, Alexandru-Ştefan Băicoianu-Nițescu, Robert Mihai Enache, Ioana Gabriela Lupescu

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Mapping urban green structures using object-based analysis of satellite imagery: A review by Shivesh Kishore Karan, Bjørn Tobias Borchsenius, Misganu Debella-Gilo, Jonathan Rizzi

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AI-Driven Background Segmentation for High-Throughput 3D Plant Scans by Serkan Kartal, Jan Masner, Jana Kholova, Alexander Galba, Tharanya Murugesan, Rekha Baddam, Vojtech Mikes, Eva Kanska

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Advanced Segmentation of Gastrointestinal (GI) Cancer Disease Using a Novel U-MaskNet Model by Aditya Pal, Hari Mohan Rai, Mohamed Ben Haj Frej, Abdul Razaque

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Flight-Safe Inference: SVD-Compressed LSTM Acceleration for Real-Time UAV Engine Monitoring Using Custom FPGA Hardware Architecture by Sreevalliputhuru Siri Priya, Penneru Shaswathi Sanjana, Rama Muni Reddy Yanamala, Rayappa David Amar Raj, Archana Pallakonda, Christian Napoli, Cristian Randieri

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Multimodal Brain Tumor Classification Using Convolutional Tumnet Architecture by M. Padma Usha, G. Kannan, M. Ramamoorthy

“…In this paper, multimodal fused imaging with classification and segmentation for brain tumors was proposed using the deep learning method. …”
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Integration of Probability Maps into Machine Learning Models for Enhanced Crack Segmentation in Concrete Bridges by Volodymyr Tyvoniuk, Roman Trach, Yuliia Trach

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Reliable Tuberculosis Detection Using Chest X-Ray With Deep Learning, Segmentation and Visualization by Tawsifur Rahman, Amith Khandakar, Muhammad Abdul Kadir, Khandaker Rejaul Islam, Khandakar F. Islam, Rashid Mazhar, Tahir Hamid, Mohammad Tariqul Islam, Saad Kashem, Zaid Bin Mahbub, Mohamed Arselene Ayari, Muhammad E. H. Chowdhury

“…Accurate and early detection of TB is very important, otherwise, it could be life-threatening. In this work, we have detected TB reliably from the chest X-ray images using image pre-processing, data augmentation, image segmentation, and deep-learning classification techniques. …”
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A Fractal Curve-Inspired Framework for Enhanced Semantic Segmentation of Remote Sensing Images by Xinhua Wang, Botao Yuan, Zhuang Li, Heqi Wang

“…The classification and recognition of features play a vital role in production and daily life; however, the current semantic segmentation of remote sensing images is hampered by background interference and other factors, leading to issues such as fuzzy boundary segmentation. …”
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