Physical bases for determination of scattering kernels from incomplete data in grid-less X-ray imaging by A. Yu. Danyk, O. O. Sudakov

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CNN-based vane-type vortex generator modelling by Koldo Portal-Porras, Unai Fernandez-Gamiz, Ekaitz Zulueta, Roberto Garcia-Fernandez, Xabier Uralde-Guinea

“…The simplicity and accuracy of Computational Fluid Dynamics (CFD) tools have made them the most widely used method for solving fluid dynamics problems. …”
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Comparative Analysis of Deep Learning Architectures for Macular Hole Segmentation in OCT Images: A Performance Evaluation of U-Net Variants by H. M. S. S. Herath, S. L. P. Yasakethu, Nuwan Madusanka, Myunggi Yi, Byeong-Il Lee

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A Method of Fatigue Driving State Detection Based on Deep Learning by XIONG Qunfang, LIN Jun, YUE Wei

“…Current domestic and overseas fatigue recognition algorithms are implemented using fatigue features which are mostly singular and man-made. Most of those algorithms have complex structure, low efficiency and weak adaptability in face of driver’s individual behavior habit. …”
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RACNet: risk assessment Net of cervical lesions in colposcopic images by Tianxiang Xu, Peizhong Liu, Ping Li, Xiaoxia Wang, Huifeng Xue, JingMing Guo, Binhua Dong, Pengming Sun

“…The RACNet was compared with the most advanced methods and colposcopists under the same condition. …”
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Models, systems, networks in economics, engineering, nature and society by L.Yu. Кrivonogov1, S.F. Levin, I.S. Inomboev, D.V. Papshev

“…The aim of the study is to create and evaluate a convolutional neural network model for automatic ECG signals classification in 12 standard leads to identify the most common and dangerous cardiovascular diseases. …”

Vision-Based UAV Localization on Various Viewpoints by Yee-Ming Ooi, Che-Cheng Chang, Yu-Min Su, Chiao-Ming Chang

“…The model achieves only 17% accuracy without applying rotational augmentation in the most practical scenario. However, the accuracy significantly improves by incorporating rotational augmentation with 15-degree increments to 95%.…”
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Knowledge graph-based entity alignment with unified representation for auditing by Youhua Zhou, Xueming Yan, Han Huang, Zhifeng Hao, Haofeng Zhu, Fangqing Liu

“…Entity alignment involves linking entity pairs with the same real-world identity and aims to integrate heterogeneous knowledge across different knowledge graphs. However, most existing works do not effectively combine both attribute and relation representations into a unified framework for entity alignment, which is essential to link entities within an audit knowledge graph accurately. …”
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Detecting Phishing URLs Based on a Deep Learning Approach to Prevent Cyber-Attacks by Qazi Emad ul Haq, Muhammad Hamza Faheem, Iftikhar Ahmad

“…Phishing is one of the most widely observed types of internet cyber-attack, through which hundreds of clients using different internet services are targeted every day through different replicated websites. …”
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Ada-GCNLSTM: An adaptive urban crime spatiotemporal prediction model by Miaoxuan Shan, Chunlin Ye, Peng Chen, Shufan Peng

“…While many effective spatiotemporal crime prediction methods have been proposed, most overlook this issue, reducing their ability to generalize. …”
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Nonlinear multi-head cross-attention network and programmable gradient information for gaze estimation by Yujie Li, Yuhang Hong, Ziwen Wang, Jiahui Chen, Rongjie Liu, Shuxue Ding, Benying Tan

“…Recent gaze estimation methods are primarily based on convolutional neural networks (CNNs) or attention Transformers. …”
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MobileNet-HeX: Heterogeneous Ensemble of MobileNet eXperts for Efficient and Scalable Vision Model Optimization by Emmanuel Pintelas, Ioannis E. Livieris, Vasilis Tampakas, Panagiotis Pintelas

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Simultaneous single image super‐resolution and blind Gaussian denoising via slim ghost full‐frequency residual blocks by Saghar Farhangfar, Aryaz Baradarani, Mohammad Asadpour, Mohammad Ali Balafar, Roman Gr. Maev

“…Abstract Given that super‐resolution (SR) aims to recover lost information, and low‐resolution (LR) images in real‐world conditions might be corrupted with multiple degradations, considering basic bicubic down‐sampling as the sole degradation significantly limits the performance of most existing SR models. This paper presents a model for simultaneous super‐resolution and blind additive white Gaussian noise (AWGN) denoising with two components (netdeg and netSR) that is based on a generative adversarial network (GAN) to achieve detailed results. netdeg, featuring residual and innovative cost‐effective ghost residual blocks with a frequency separation module for obtaining long‐range information, blindly restores a clean version of the LR image. netSR leverages slim ghost full‐frequency residual blocks to process low‐frequency (LF) and high‐frequency (HF) information via static large convolutions and pixel‐wise highlighted input‐adaptive dynamic convolutions, respectively. …”
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Skin Cancer Cell Detection using Image Processing by Taskin Sabit, Faiza Tasnim, Sadia Afrin Sara, Sharia Tasnim Adrita, Maisha Tarannum

“…Early diagnosis and precise detection of skin cancer represent a global health priority since this disease remains highly dangerous while being among the most frequent ones. This research investigates the effectiveness of deep learning techniques, specifically Convolutional Neural Networks (CNN) and the VGG16 architecture, for skin cancer detection and classification. …”
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HLQ: Hardware-Friendly Logarithmic Quantization Aware Training for Power-Efficient Low-Precision CNN Models by Dahun Choi, Juntae Park, Hyun Kim

“…Unlike the existing linear quantization, logarithmic quantization has the advantage that the multiply-accumulate (MAC) operation in the convolution (CONV) operation, which occupies most of the CNNs, can be replaced with the addition operation and is suitable for low-precision quantization. …”
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EfficientNet-B0 outperforms other CNNs in image-based five-class embryo grading: a comparative analysis by Vincent Jaehyun Shim, Hosup Shim, Sangho Roh

“…Gradient-weighted Class Activation Mapping was used to interpret the models’ decision-making processes, revealing that the most successful models predominantly focused on the inner cell mass, a critical determinant of embryo quality. …”
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Classification and Physical Characteristic Analysis of Fermi-GBM Gamma-Ray Bursts Based on Deep Learning by Jia-Ming Chen, Ke-Rui Zhu, Zhao-Yang Peng, Li Zhang

“…The analysis also shows that most GRBs associated with kilonovae belong to the S type, while those associated with supernovae are predominantly L type, with few exceptions. …”
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A colonic polyps detection algorithm based on an improved YOLOv5s by Jianjun Li, Jinhui Zhao, Yifan Wang, Jinhui Zhu, Yanhong Wei, Junjiang Zhu, Xiaolu Li, Shubin Yan, Qichun Zhang

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A New Way to Identify Mastitis in Cows Using Artificial Intelligence by Rodes Angelo Batista da Silva, Héliton Pandorfi, Filipe Rolim Cordeiro, Rodrigo Gabriel Ferreira Soares, Victor Wanderley Costa de Medeiros, Gledson Luiz Pontes de Almeida, José Antonio Delfino Barbosa Filho, Gabriel Thales Barboza Marinho, Marcos Vinícius da Silva

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Predictive and Explainable Artificial Intelligence for Weight Loss After Sleeve Gastrectomy: Insights from Wide and Deep Learning with Medical Image and Non-Image Data by Jaechan Park, Sungsoo Park, Kwang-Sig Lee, Yeongkeun Kwon

“…Here, the WAD model combined a convolutional neural network (CNN) for image data and a linear layer for non-image data (EMR). …”
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