Predicting lung metastasis in high-grade osteosarcoma: The role of computed tomography angiography (CTA) signs with a focus on vascular wrapping and the intratumoral vascular netwo... by Zhendong Luo, Tao Ai, Zhiqiang Liu, Litong He, Yanzhen Hou, Yulin Li, Ziyan Zhou, Xinping Shen

“…Methods: A retrospective study was conducted involving 89 consecutive patients with osteosarcoma. Clinical features and CTA signs, including age, gender, laterality, primary site, type of bone destruction, T stage, periosteal reaction, tumor length, bone marrow involved length, vascular wrapping, and intratumoral vascular network, were evaluated. …”
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Fast Fourier Asymmetric Context Aggregation Network: A Controllable Photo-Realistic Clothing Image Synthesis Method Using Asymmetric Context Aggregation Mechanism by Haopeng Lei, Ying Hu, Mingwen Wang, Meihai Ding, Zhen Li, Guoliang Luo

“…To address these issues, we propose the Fast Fourier Asymmetric Context Aggregation Network (FCAN), a novel image generation network designed to achieve controllable clothing image synthesis guided by design sketches and texture patches. …”
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Improved faster R-CNN for steel surface defect detection in industrial quality control by Yuefeng Leng, Jiazhi Liu

“…The proposed framework incorporates a feature fusion module and lightweight channel attention mechanism between Feature Pyramid Networks (FPN) and Region Proposal Network (RPN), substantially augmenting subtle feature extraction capabilities. …”
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Deep Multimodal-Interactive Document Summarization Network and Its Cross-Modal Text–Image Retrieval Application for Future Smart City Information Management Systems by Wenhui Yu, Gengshen Wu, Jungong Han

“…To address this, a deep multimodal-interactive network is proposed for accurate document summarization. …”
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A Low-Cost AI-Powered System for Early Detection of Diabetic Retinopathy and Ocular Diseases in Resource Limited Settings by Harpreet Vohra, Mohammad Kamrul Hasan, Siti Norul Huda Sheikh Abdullah, Shayla Islam, Abdul Hadi Abd Rahman, Shreya N. Bhojake, Dhruv Bobal, Awal Kaur Gandhi, Muskan, Chandramohan Dhasarathan

“…These images are analyzed using advanced Convolutional Neural Networks to determine the cases of people suffering from eye issues: Age-related vascular degeneration (AMD), Diabetic retinopathy (DR), and Glaucoma. …”
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Real-time monitoring and analysis of hydraulic fracturing in surface well using microseismic technology: Case insights and methodological advances by Yanan Qian, Ting Liu, Cheng Zhai, Hongda Wen, Yuebing Zhang, Menghao Zheng, Hexiang Xu, Dongyong Xing, Xinke Gan

“…Through a case analysis, this study examines the spatiotemporal evolution of microseismic (MS) events, energy characteristics, volumetric features, and fracture network development in surface well hydraulic fracturing. …”
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Pyramidal attention-based T network for brain tumor classification: a comprehensive analysis of transfer learning approaches for clinically reliable and reliable AI hybrid approach... by Tathagat Banerjee, Prachi Chhabra, Manoj Kumar, Abhay Kumar, Kumar Abhishek, Mohd. Asif Shah

“…In this paper, we introduce a novel Pyramidal Attention-Based bi-partitioned T Network (PABT-Net) that combines the hierarchical pyramidal attention mechanism and T-block based bi-partitioned feature extraction, and a self-convolutional dilated neural classifier as the final task. …”
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The GAN Spatiotemporal Fusion Model Based on Multiscale Convolution and Attention Mechanism for Remote Sensing Images by Youping Xie, Jun Hu, Kang He, Li Cao, Kaijun Yang, Luo Chen

“…In the feature extraction stage, multiscale convolutional attention network (MSCAN) captures detailed features across multiple scales, dealing with spatial dependencies and long-distance relationships within the images. …”
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ACT-FRCNN: Progress Towards Transformer-Based Object Detection by Sukana Zulfqar, Zenab Elgamal, Muhammad Azam Zia, Abdul Razzaq, Sami Ullah, Hussain Dawood

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A Study on CNN-Based and Handcrafted Extraction Methods with Machine Learning for Automated Classification of Breast Tumors from Ultrasound Images by Mohamed Benaouali, Mohamed Bentoumi, Mansour Abed, Malika Mimi, Abdelmalik Taleb-Ahmed

“… In this paper, we present an efficient procedure for automatically classifying ultrasound images of benign and malignant breast tumors. We evaluated our approach using four openly available datasets and investigated two categories of feature extraction methods: handcrafted methods (Local Binary Pattern (LBP), Histogram of Oriented Gradients (HOG)) and methods based on convolutional neural network (CNN) models. …”
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Efficient Hybrid-Robust Approach for Cancer Biomarker Discovery Using Omics Data by Karima Sid, Soumia Zertal, Mohamed Batouche, Soumeya Zerabi

“…In each step, a combination of techniques and algorithms is used to improve the results in terms of stability and/or accuracy. The proposal is evaluated and tested according to different scenarios; using thirteen gene expression datasets and two classifiers: Artificial Neural Network (ANN) and Naïve Bayes (NB). …”
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Proto-Caps: interpretable medical image classification using prototype learning and privileged information by Luisa Gallée, Catharina Silvia Lisson, Timo Ropinski, Meinrad Beer, Michael Götz

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Artificial Intelligence in the Analysis of Upper Gastrointestinal Disorders by Chang Seok Bang

“…In the past, conventional machine learning was applied to analyze tabulated medical data while deep learning was applied to study afflictions such as gastrointestinal disorders. Neural networks were used to detect, classify, and delineate various images of lesions because the local feature selection and optimization of the deep learning model enabled accurate image analysis. …”
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Chinese Paper-Cutting Style Transfer via Vision Transformer by Chao Wu, Yao Ren, Yuying Zhou, Ming Lou, Qing Zhang

“…Therefore, this paper proposes a new method for Chinese paper-cutting style transformation based on the Transformer, aiming at realizing the efficient transformation of Chinese paper-cutting art styles. Specifically, the network consists of a frequency-domain mixture block and a multi-level feature contrastive learning module. …”
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HiImp-SMI: an implicit transformer framework with high-frequency adapter for medical image segmentation by Lianchao Huang, Feng Peng, Binghao Huang, Yinghong Cao

“…The entire network is trained in a supervised end-to-end manner, with frequency-adaptive modules integrated into the encoding stages of the Transformer backbone. …”
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Enhanced Plant Leaf Classification over a Large Number of Classes Using Machine Learning by Ersin Elbasi, Ahmet E. Topcu, Elda Cina, Aymen I. Zreikat, Ahmed Shdefat, Chamseddine Zaki, Wiem Abdelbaki

“…The Cope Leaf Dataset offers a comprehensive collection of leaf images from various plant species, enabling the development and evaluation of advanced classification algorithms. This study presents a robust methodology for classifying leaf images within the Cope Leaf Dataset by enhancing the feature extraction and selection process. …”
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A CNN-Based Downscaling Model for Macau Temperature Prediction Using ERA5 Reanalysis Data by Ningqing Pang, Hoiio Kong, Chanseng Wong, Zijun Li, Yu Du, Jeremy Cheuk-Hin Leung

“…In this study, a lightweight downscaling method incorporating a convolutional neural network is proposed to construct a high-resolution temperature prediction model for the Macau region based on ERA5 reanalysis data. …”
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A data-driven approach to predict fracture intensity using machine learning for presalt carbonate reservoirs: A feasibility study in the Mero Field, Santos Basin, Brazil by Eberton Rodrigues de Oliveira Neto, Fábio Júnior Damasceno Fernandes, Tuany Younis Abdul Fatah, Raquel Macedo Dias, Zoraida Roxana Tejada da Piedade, Antonio Fernando Menezes Freire, Wagner Moreira Lupinacci

“…The distance to fault is measured using the fault probability volume estimated by a pre-trained convolutional neural network (CNN). We evaluate the effectiveness of this data-driven approach employing two tree-ensemble models, eXtreme Gradient Boosting (XGBoost) and Random Forest, to estimate the volumetric fracture intensity (P32) in the wells. …”
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Graph Contrastive Pre-training for Anti-money Laundering by Hanbin Lu, Haosen Wang

“…KNN view provides implicit interactions to mitigate the link sparsity in the transaction network. Moreover, we extend the positive sample set using connected neighbors and node pairs with similar features to further enhance the expressiveness of the model. …”
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CoAt-Set: Transformed coordinated attack dataset for collaborative intrusion detection simulationMendeley Data by Aulia Arif Wardana, Grzegorz Kołaczek, Parman Sukarno

“…CoAt-Set focuses on coordinated attack scenarios such as large-scale stealthy scans, worm outbreaks, and distributed denial-of-service (DDoS) attacks, simulating realistic and high-impact threats that commonly observed in modern networks. The transformation process involved organizing coordinated attack behaviors and providing detailed annotations and network traffic features, enhancing its relevance for anomaly detection in collaborative environments. …”
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