3L-YOLO: A Lightweight Low-Light Object Detection Algorithm by Zhenqi Han, Zhen Yue, Lizhuang Liu

“…First, we introduce switchable atrous convolution (SAConv) into the C2f module of YOLOv8n, improving the model’s ability to efficiently capture global contextual information. …”
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YOLO-Ssboat: Super-Small Ship Detection Network for Large-Scale Aerial and Remote Sensing Scenes by Yiliang Zeng, Xiuhong Wang, Jinlin Zou, Hongtao Wu

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A dynamic attention mechanism for road extraction from high-resolution remote sensing imagery using feature fusion by Haoming Bai, Chao Ren, Zhenzhong Huang, Yao Gu

“…The dual-branch encoder leverages dual convolutions and multi-head deep convolutions to extract fundamental features and capture fine-grained details. …”
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DMF-YOLO: Dynamic Multi-Scale Feature Fusion Network-Driven Small Target Detection in UAV Aerial Images by Xiaojia Yan, Shiyan Sun, Huimin Zhu, Qingping Hu, Wenjian Ying, Yinglei Li

“…To address these issues, this paper proposes DMF-YOLO, a high-precision detection network based on YOLOv10 improvements. First, we design Dynamic Dilated Snake Convolution (DDSConv) to adaptively adjust the receptive field and dilation rate of convolution kernels, enhancing local feature extraction for small targets with weak textures. …”
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A novel anomaly detection method for multimodal WSN data flow via a dynamic graph neural network by Qinghao Zhang, Miao Ye, Xiaofang Deng

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A Dynamic Adaptive Framework for Remote Sensing Imagery Superpixel Segmentation and Classification via Dual-Branch Feature Learning by Wangtun Yang, Yang Zhang, Heng Zhang, Liangzhi Li

“…The proposed method introduces a dynamic adaptive quantization framework and bit mapping modules, enabling the model to flexibly adapt to various bit-width configurations. …”
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Deep learning approach to the estimation of the ratio of reproductive modes in a partially clonal population by T. A. Nikolaeva, A. A. Poroshina, D. Yu. Sherbakov

“…This research focuses on exploring the coexistence patterns of sexual and asexual reproduction within a single species. We developed a convolutional neural network model specifically designed to analyze the dynamics of populations exhibiting mixed reproductive strategies within changing environments. …”
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From Prediction to Explanation: Using Explainable AI to Understand Satellite-Based Riot Forecasting Models by Scott Warnke, Daniel Runfola

“…First, a ResNet18 convolutional neural network achieved 89% accuracy in distinguishing riot and non-riot urban areas. …”
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Resultant Force on Grains of a Real Sand Dune: How to Measure It? by R. F. Miotto, C. A. Alvarez, D. S. Borges, W. R. Wolf, E. M. Franklin

“…Abstract Barchan dunes usually appear under the action of one‐directional fluid flows, being found on Earth, Mars, and other celestial bodies; however, although ubiquitous in nature, understanding dune dynamics at the grain scale is challenging due to the vast number of grains involved. …”
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Individual Contribution-Based Spatial-Temporal Attention on Skeleton Sequences for Human Interaction Recognition by Xing Liu, Bo Gao

“…Skeleton-based human interaction recognition has gained increasing attention due to its ability to capture complex multi-person dynamics. Significant progress has been made in interaction recognition research, but challenges remain. …”
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Heterogeneous network drug-target interaction prediction model based on graph wavelet transform and multi-level contrastive learning by Wenfeng Dai, Yanhong Wang, Shuai Yan, Qingzhi Yu, Xiang Cheng

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Energy efficiency and system complexity analysis of CNN based hybrid precoding for cell-free massive MIMO under terahertz communication by Tadele A. Abose, Yitbarek A. Mekonen, Binyam G. Assefa, Naol W. Gudeta

“…However, this integration faces significant challenges, such as dynamic and unpredictable channel behavior. Traditional channel estimation techniques are inadequate for handling these dynamic conditions. …”
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Lightweight AI Models in Mineral Processing: Classifying Hydrocyclone Underflow With ResNet-18 and MobileViT-V2 by Tomas Henrique Coelho E Silva, Ricardo Augusto Rabelo Oliveira

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Comparative Analysis of Machine Learning Models for Predicting Contaminant Concentration Distributions in Hospital Wards by Chonggang Zhou, Yunfei Ding

“…In this study, contaminant concentration data from hospital wards were obtained through experimentally validated computational fluid dynamics (CFD) simulations. Four common machine learning models—multiple linear regression (MLR), support vector regression (SVR), backpropagation (BP) neural network, and convolutional neural network (CNN)—were employed to predict the distribution of contaminants within the wards. …”
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Temporal–Spatial Partial Differential Equation Modeling of Land Cover Dynamics via Satellite Image Time Series and Sparse Regression by Ming Kang, Zheng Zhang, Zhitao Zhao, Keli Shi, Junfang Zhao, Ping Tang

“…Land cover dynamics play a critical role in understanding environmental changes, but accurately modeling these dynamics remains a challenge due to the complex interactions between temporal and spatial factors. …”
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Enhancing classification efficiency in capsule networks through windowed routing: tackling gradient vanishing, dynamic routing, and computational complexity challenges by Gangqi Chen, Zhaoyong Mao, Junge Shen, Dongdong Hou

“…Abstract Capsule networks overcome the two drawbacks of convolutional neural networks: weak rotated object recognition and poor spatial discrimination. …”
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A fiber optic refractive index sensor with extremely high dynamic range utilizing deep learning-speckle pattern imaging by Hüsamettin Şerbetçi, Isa Navruz, Fikret Ari

“…In this paper, a tapered optical fiber sensor with high precision measurement capability in a wide dynamic range has been proposed and experimentally demonstrated. …”
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Performance for rotor system of hybrid electromagnetic bearing and elastic foil gas bearing with dynamic characteristics analysis under deep learning. by Xiangxi Du, Yanhua Sun

“…The bearing-rotor system is prone to faults during operation, so it is necessary to analyze the dynamic characteristics of the bearing-rotor system to discuss the optimal structure of the convolutional neural network (CNN) in system fault detection and classification. …”
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Enhanced YOLOv7-Tiny for Small-Scale Fire Detection via Multi-Scale Channel Spatial Attention and Dynamic Upsampling by Shihao Wu, Yi Xia

“…To improve detection performance for small targets, we introduce the DySample module, a dynamic upsampling strategy that enhances feature map resolution. …”
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Enhancing Visual Perception in Immersive VR and AR Environments: AI-Driven Color and Clarity Adjustments Under Dynamic Lighting Conditions by Maryam Abbasi, Paulo Váz, José Silva, Pedro Martins

“…The visual fidelity of virtual reality (VR) and augmented reality (AR) environments is essential for user immersion and comfort. Dynamic lighting often leads to chromatic distortions and reduced clarity, causing discomfort and disrupting user experience. …”
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