LH-YOLO: A Lightweight and High-Precision SAR Ship Detection Model Based on the Improved YOLOv8n by Qi Cao, Hang Chen, Shang Wang, Yongqiang Wang, Haisheng Fu, Zhenjiao Chen, Feng Liang

“…LH-YOLO features only 1.862 M parameters, representing a 38.1% reduction compared to YOLOv8n. …”
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Express method for contactless measurement of parameters of thermoelectric materials by A. A. Ashcheulov, I. A. Buchkovskii, I. S. Romanyuk

“…Its distinctive feature is the ability to determine the symmetric and asymmetric components of the electric conductivity of the material values. …”
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Classifying seismic event parameters using artificial intelligence by Abbas Maazallahi, Kameron Bustos, Mohammad Amir Salari, Eli Snir, Payam Norouzzadeh, Bahareh Rahmani

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YOLO-Dynamic: A Detection Algorithm for Spaceborne Dynamic Objects by Haiying Zhang, Zhengyang Li, Chunyan Wang

“…SC_Block_C2f, developed in this study, integrates StarNet and Convolutional Gated Linear Unit (CGLU) operations, improving small-object recognition and feature extraction. Meanwhile, LASF_Neck employs a lightweight multi-scale architecture for optimized feature fusion and faster detection. …”
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Evaluation and comparison of methods for neuronal parameter optimization using the Neuroptimus software framework. by Máté Mohácsi, Márk Patrik Török, Sára Sáray, Luca Tar, Gábor Farkas, Szabolcs Káli

“…Neuroptimus also offers several features to support more advanced usage, including the ability to run most algorithms in parallel, which allows it to take advantage of high-performance computing architectures. …”
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A malware detection method with function parameters encoding and function dependency modeling by Ronghao Hou, Dongjie Liu, Xiaobo Jin, Jian Weng, Guanggang Geng

“…Specifically, we first design a parameter encoder to convert various types of function parameters into feature vectors, and then discretize various parameter features through clustering methods to enhance the representation of API encoding. …”
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Full-process aerosol jet printing modelling: achieving high-fidelity simulation via coupling jetting and deposition by Yufeng Jin, Hao Yi, Huajun Cao, Xianshan Dong

“…Various factors – including printing parameters and ink properties – affect the printing features. …”
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Enhanced detection of malaria infected red blood cells through phase driven classification by Charlotte Kyeremah, Aditya S. Paul, Daniel Haehn, Manoj T. Duraisingh, Chandra S. Yelleswarapu

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Credibility-Adjusted Data-Conscious Clustering Method for Robust EEG Signal Analysis by Fatemeh Divan, Teh Ying Wah, Kheng Seang Lim, Ali Seyed Shirkhorshidi

“…A grid search framework optimizes clustering parameters, and preprocessing techniques (Fourier Transform, Wavelet Transform, and Gaussian filtering) improve feature separability. …”
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Network Security Situational Awareness Based on Improved Particle Swarm Algorithm and Bidirectional Long Short-Term Memory Modeling by Peng Zheng, Yun Cheng, Wei Zhu, Bo Liu, Shuhong Liu, Shijie Wang, Jinyin Bai

“…By gathering and organizing critical information within the network, an encapsulated Wrapper feature selection algorithm is utilized for the extraction of element features. …”
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Ripe-Detection: A Lightweight Method for Strawberry Ripeness Detection by Helong Yu, Cheng Qian, Zhenyang Chen, Jing Chen, Yuxin Zhao

“…To address these limitations, this study proposes Ripe-Detection, a novel lightweight object detection framework integrating three key innovations: a PEDblock detection head architecture with depth-adaptive feature learning capability, an ADown downsampling method for enhanced detail perception with reduced computational overhead, and BiFPN-based hierarchical feature fusion with learnable weighting mechanisms. …”
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Preoperative prediction value of 2.5D deep learning model based on contrast-enhanced CT for lymphovascular invasion of gastric cancer by Xiao Sun, Pei Wang, Rui Ding, Li Ma, Huairong Zhang, Li Zhu

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In Situ Capture of High-Temperature Precipitate Phases in Ti-48Al-2Cr-2Nb Alloy Using Convolutional Neural Networks by Xiaolei Li, Chuanqing Huang, Sen Zhao, Linlin Cui, Shirui Guo, Bo Zheng, Yinghao Cui, Yongqian Chen, Yue Zhao, Lujun Cui, Chunjie Xu

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YOLOv8-SC: an improved seafood target-detection model by Zhaofeng Cong, Fusheng Yu

“…It replaces the traditional C2f module with the Sequential Optimized Squeeze Excitation (SOSE) module to streamline the structure and reduce parameters. The model adopts a Bi-directional Feature Pyramid Network (BiFPN)-based architecture to improve accuracy without adding detection heads. …”
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RDM-YOLO: A Lightweight Multi-Scale Model for Real-Time Behavior Recognition of Fourth Instar Silkworms in Sericulture by Jinye Gao, Jun Sun, Xiaohong Wu, Chunxia Dai

“…Methodologically, Res2Net blocks are first integrated into the backbone network to enable hierarchical residual connections, expanding receptive fields and improving multi-scale feature representation. Second, standard convolutional layers are replaced with distribution shifting convolution (DSConv), leveraging dynamic sparsity and quantization mechanisms to reduce computational complexity. …”
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Clinical case of a patient with pulmonary capillary hemangiomatosis: rapid progression or lost time? by E. A. Devetyarova, T. V. Martynyuk, A. A. Dyuzhikov, E. V. Paschenko, A. V. Dyuzhikova

“…The article describes a clinical case of a 37-year-old patient with pulmonary capillary hemangiomatosis of functional class IV according to the WHO classification with difficulties of diagnostic search and features of PAH-specific therapy.Pulmonary arterial hypertension - group 1 in the clinical classification is represented by several forms of pathology, including very rare diseases such as pulmonary veno-occlusive disease and pulmonary capillary hemangiomatosis.The difficulties of diagnostic search consist in the absence of specific symptoms, a variety of interstitial or focal changes according to spiral computed tomography, and the final diagnosis can be made only after performing a lung biopsy, which is associated with a high risk of possible complications. …”
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PONet: A Compact RGB-IR Fusion Network for Vehicle Detection on OrangePi AIpro by Junyu Huang, Jialing Lian, Fangyu Cao, Jiawei Chen, Renbo Luo, Jinxin Yang, Qian Shi

“…PONet incorporates Polarized Self-Attention to improve feature adaptability and representation with minimal computational overhead. …”
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Deep Learning Innovations for Underwater Waste Detection: An In-Depth Analysis by Jaskaran Singh Walia, Kavietha Haridass, L. K. Pavithra

“…We investigate multiple architectures, including YOLOv8n, YOLOv7, YOLOv6s, YOLOv5s, Faster R-CNN, and Mask R-CNN, analyzing key parameters such as mean average precision (mAP), inference speed, and computational efficiency. …”
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Methodology and Algorithm of Multicomponent Analysis of Positron Annihilation Spectra for Nanostructured Functional Materials by H.I. Klym, A.I. Ivanusa, Yu.M. Kostiv, D.O. Chalyy, T.I. Tkachuk, R.B. Dunets, I.I. Vasylchyshyn

“…Methodology for treatment of positron annihilation lifetime spectra by LT computer program in the nanostructured ceramic materials was proposed. …”
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Exploration of geo-spatial data and machine learning algorithms for robust wildfire occurrence prediction by Svetlana Illarionova, Dmitrii Shadrin, Fedor Gubanov, Mikhail Shutov, Usman Tasuev, Ksenia Evteeva, Maksim Mironenko, Evgeny Burnaev

“…Conventional approaches primarily rely on the computation of fire indices based on weather conditions. …”
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