SubsurfaceBreaks v. 1.0: a supervised detection of fault-related structures on triangulated models of subsurface homoclinal interfaces by M. P. Michalak, C. Gerhards, P. Menzel

“…<p>The study presents a novel approach for fault detection on subsurface geological homoclinal interfaces (slopes) using a supervised learning algorithm and careful input variable (feature) selection. Synthetic faulted slopes are generated using Delaunay triangulation via the Computational Geometry Algorithms Library (CGAL), allowing for adjustments of parameters. …”
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Weak Fault Detection for Rolling Bearings in Varying Working Conditions through the Second-Order Stochastic Resonance Method with Barrier Height Optimization by Huaitao Shi, Yangyang Li, Peng Zhou, Shenghao Tong, Liang Guo, Baicheng Li

“…The potential well functions are mostly set fixed to reduce computational complexity, and the SR methods with fixed potential well parameters have better performances in stable working conditions. …”
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Sparse Deep Neural Network for Encoding and Decoding the Structural Connectome by Satya P. Singh, Sukrit Gupta, Jagath C. Rajapakse

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A Lightweight Cotton Field Weed Detection Model Enhanced with EfficientNet and Attention Mechanisms by Lu Zheng, Lyujia Long, Chengao Zhu, Mengmeng Jia, Pingting Chen, Jun Tie

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Silkworm segmentation based on encoder-decoder structure by Huimin Zhuang, Zicheng Liu, Jianping Dong, Dequan Guo, Guoquan Yuan, Bo Liu, Yu Liu

“…Compared with the U-Net model, the computational complexity is reduced by 84.25 % (0.855 GFLOPs vs. 5.427 GFLOPs), and the number of parameters is reduced by 95.32 % (0.67 M vs. 14.33 M).…”
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Advancing Skin Disease Diagnosis: A Multimodal Approach Utilizing Telegram Api Token Chatbot for Text and Image Analysis in Skin Disease Classification by Modigari Narendra, T. S. Harshini, L. Jani Anbarasi

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BSMD-YOLOv8: Enhancing YOLOv8 for Book Signature Marks Detection by Long Guo, Lubin Wang, Qiang Yu, Xiaolan Xie

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Low-Damage Grasp Method for Plug Seedlings Based on Machine Vision and Deep Learning by Fengwei Yuan, Gengzhen Ren, Zhang Xiao, Erjie Sun, Guoning Ma, Shuaiyin Chen, Zhenlong Li, Zhenhong Zou, Xiangjiang Wang

“…The lightweight network Mobilenet is used as the feature extraction network to reduce the number of parameters of the network. …”
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Eeg-based detection of epileptic seizures in patients with disabilities using a novel attention-driven deep learning framework with SHAP interpretability by Tawfeeq Shawly, Ahmed A. Alsheikhy

“…Nevertheless, current models frequently face challenges related to feature selection, interpretability, and computational demands. …”
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CGDINet: A Deep Learning-Based Salient Object Detection Algorithm by Chengyu Hu, Jianxin Guo, Hanfei Xie, Qing Zhu, Baoxi Yuan, Yujie Gao, Xiangyang Ma, Jialu Chen, Juan Tian

“…The results show that CGDINet outperforms other mainstream significance object detection models in evaluation metrics such as <inline-formula> <tex-math notation="LaTeX">${\mathrm {maxF}}_{\mathrm {\beta }}$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$\mathrm {S}_{\mathrm {\alpha }}$ </tex-math></inline-formula>, and MAE, with almost no increase in computational cost (FLOPs) and parameters. The experimental results validate that CGDINet can effectively address the issues of incomplete global feature extraction and insufficient attention to key areas, thereby significantly enhancing the performance of significance object detection.…”
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The quartic anharmonic oscillator – an oscillator-basis expansion approach. II. Study of the wave functions and acceleration of the expansions convergence by V. A. Babenko, A. V. Nesterov

“…The method we propose for studying the model, based on expanding the system's wave function in a complete set of harmonic oscillator eigenfunctions, facilitates a thorough analysis and evaluation of all parameters and features of the corresponding quantum systems. …”
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Investigating multi-directional flow dynamics in three-way ball valves: a CFD-based study by Amol Dhumal, Nitin Ambhore, Gaurav Sanap, Tanmay Patil, Vishal Sanap, Aryan Kadu

“…Abstract The objective of this study is to analyze a three-way ball valve using computational fluid dynamic simulations in ANSYS Fluent to achieve better flow control and improve the efficiency of the system. …”
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Positron emission tomography imaging biomarker and artificial intelligence for the characterization of solitary pulmonary nodule by Ashish Kumar Jha, Ashish Kumar Jha, Umeshkumar Baburao Sherkhane, Umeshkumar Baburao Sherkhane, Nilendu C. Purandare, Nilendu C. Purandare, Leonard Wee, Andre Dekker, Venkatesh Rangarajan, Venkatesh Rangarajan

“…BackgroundThe characterization of solitary pulmonary nodules (SPNs) as malignant or benign remains a diagnostic challenge using conventional imaging parameters. The literature suggests using combined Positron Emission Tomography (PET) and Computed Tomography (CT) to characterise a SPN. …”
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Fusion of Multimodal Audio Data for Enhanced Speaker Identification Using Kolmogorov-Arnold Networks by Aryaman Tamotia, Dhruv Shantu Karmokar, Rethi Komal, K. Khadar Nawas, A. Shahina, A. Nayeemulla Khan

“…Although the classical deep learning methods are effective, they have rather high computational cost, which leads to usually cumbersome parameter tuning processes and hence reduce their applicability to real-world deployments. …”
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Flat U-Net: An Efficient Ultralightweight Model for Solar Filament Segmentation in Full-disk Hα Images by GaoFei Zhu, GangHua Lin, Xiao Yang, Cheng Zeng

“…Each block effectively optimizes the channel features from the previous layer, significantly reducing parameters. …”
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Prediction of porosity, hardness and surface roughness in additive manufactured AlSi10Mg samples. by Fatma Alamri, Imad Barsoum, Shrinivas Bojanampati, Maher Maalouf

“…Feature importance analysis on the compiled dataset using ANN revealed that laser power and scan speed are the most important features affecting relative density (e.g., porosity) and hardness, while scan speed and layer thickness significantly impact the surface roughness of the parts. …”
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Rotten strawberry classification based on EfficientNet V2 algorithm fused with GCN and CA-Transformer by WANG Wei, YANG Shizhong, GONG Yucheng, GAO Sheng, DENG Zhaopeng

“…Finally, learning parameters were introduced on the basis of the traditional residual structure to achieve dynamic feature fusion.ResultsThe GC-EfficientNet V2 model improved the accuracy by 1.86% and the recall by 1.49% compared to the baseline model. …”
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Adaptive Noise-Powered Diffusion Model for Efficient and Accurate Object Detection by Xingyu Zou, Kaixu Han, Xinle Zhang, Wenhao Wang, Ning Wu

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High-Accuracy Recognition Method for Diseased Chicken Feces Based on Image and Text Information Fusion by Duanli Yang, Zishang Tian, Jianzhong Xi, Hui Chen, Erdong Sun, Lianzeng Wang

“…Experiments demonstrate that MMCD significantly outperforms single-modal baselines in Accuracy (+8.69%), Recall (+8.72%), Precision (+8.67%), and F1 score (+8.72%). It surpasses simple feature concatenation by 2.51–2.82% and reduces parameters by 7.5M and computations by 1.62 GFLOPs versus the base ResNet50. …”
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Steel surface defect detection method based on improved YOLOv9 by Cong Chen, Hoileong Lee, Ming Chen

“…To improve the recognition accuracy of small targets, a bidirectional feature pyramid network (BiFPN) is integrated, enabling the model to capture small target features more precisely. …”
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