A proximal policy optimization based deep reinforcement learning framework for tracking control of a flexible robotic manipulator by Joshi Kumar V, Vinodh Kumar Elumalai

“…Moreover, the major limitation of the existing policy gradient based DRL techniques is that they are computationally expensive and suffer from scalability issues for complex higher order systems. …”
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The Value of PET/CT-Based Radiomics in Predicting Adrenal Metastases in Patients with Cancer by Qiujun He, Xiangxing Kong, Xiangxi Meng, Xiuling Shen, Nan Li

“…The aim of the study was to explore the diagnostic efficacy of [18F]Fluorodeoxyglucose (FDG) positron emission tomography combined with computed tomography (PET/CT)-based radiomics in identifying adrenal metastases and to compare it with that of conventional PET/CT parameters. …”
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Establishment and Test Effect of Artificial Intelligence Optimization Model Based on Convolutional Neural Network by Chunrong Zhou, Zhenghong Jiang

“…Convolutional neural networks (CNNs) are often used in tasks involving vision processing, and unclear images can hinder the performance of convolutional neural networks and increase its computational time. Furthermore, artificial intelligence (AI) and machine learning (ML) are related technologies, which are considered a branch of computer science, which are used to simulate and enhance human intelligence. …”
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A Lightweight GCT-EEGNet for EEG-Based Individual Recognition Under Diverse Brain Conditions by Laila Alshehri, Muhammad Hussain

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A Low Complexity Linear Precoding Method for Extremely Large-Scale MIMO Systems by Salah Berra, Abderrazak Benchabane, Sourav Chakraborty, Kazuki Maruta, Rui Dinis, Marko Beko

“…As a result, spatial non-stationary features emerge as users view just a section of the antenna array, known as the visibility regions (VRs). …”
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AS-YOLO: Enhanced YOLO Using Ghost Bottleneck and Global Attention Mechanism for Apple Stem Segmentation by Na Rae Baek, Yeongwook Lee, Dong-hee Noh, Hea-Min Lee, Se Woon Cho

“…The proposed model reduces the number of parameters and enhances the computational efficiency using the ghost bottleneck while improving feature extraction capabilities using the global attention mechanism. …”
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Lightweight visible damage detection algorithm for embedded systems applied to pipeline automation equipment by Jiale Xiao, Lei Xu, Changyun Li, Ling Tang, Guogang Gao

“…The backbone of the algorithm, CSPHet, employs efficient combinatorial convolution and heterogeneous kernel convolution, incorporates a lightweight convolutional structure SL in the neck of the network, enhances the nonlinear representation and feature processing capability through channel shuffling, utilizes the lightweight self-attention mechanism Detect_SA for prediction, and employs a multilayered GhostConv to improve the computational efficiency. …”
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New Label-Free DNA Nanosensor Based on Top-Gated Metal–Ferroelectric–Metal Graphene Nanoribbon on Insulator Field-Effect Transistor: A Quantum Simulation Study by Khalil Tamersit, Abdellah Kouzou, José Rodriguez, Mohamed Abdelrahem

“…The DNA sensing principle is founded on the dielectric modulation concept. The computational method employed to evaluate the proposed nanobiosensor relies on the coupled solutions of a rigorous quantum simulation with the Landau–Khalatnikov equation, considering ballistic transport conditions. …”
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An Intelligent Fault Diagnosis Model for Rolling Bearings Based on IGTO-Optimized VMD and LSTM Networks by Xianglong Luo, Fengrong Yu, Jing Qian, Biao An, Nengpeng Duan

“…The IGTO algorithm is used to optimize the parameters of VMD and LSTM, enhancing signal decomposition and feature extraction. …”
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Three-Dimensional Magnetotelluric Forward Modeling Using Multi-Task Deep Learning with Branch Point Selection by Fei Deng, Hongyu Shi, Peifan Jiang, Xuben Wang

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HP-YOLO: A Lightweight Real-Time Human Pose Estimation Method by Haiyan Tu, Zhengkun Qiu, Kang Yang, Xiaoyue Tan, Xiujuan Zheng

“…Despite its importance, HPE faces several challenges, including high rates of false positives and negatives, stringent real-time requirements, and limited computational resources, especially in complex backgrounds. …”
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Machine Learning in the Design and Performance Prediction of Organic Framework Membranes: Methodologies, Applications, and Industrial Prospects by Tong Wu, Jiawei Zhang, Qinghao Yan, Jingxiang Wang, Hao Yang

“…Methodologically, ML workflows—spanning data construction, feature engineering, and model optimization—accelerate candidate screening, inverse design, and mechanistic interpretation, as demonstrated in gas separations and nascent liquid-phase applications. …”
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Lightweight RT-DETR with Attentional Up-Downsampling Pyramid Network by Nan Li, Xiao Han, Xingguo Song, Xu Fang, Mengming Wu, Qiulin Yu

“…However, current deep learning models struggle with accuracy and real-time performance in complex backgrounds due to high computational demands. To address this, we propose an improved RT-DETR R18 model tailored for companion robots. …”
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A YOLOv8n-T and ByteTrack-Based Dual-Area Tracking and Counting Method for Cucumber Flowers by Liyang Su, Shujuan Zhang, Hongtu Zhang, Xiangsen Meng, Xiongkui He

“…The YOLOv8n-T incorporates a Coordinate Attention (CA) mechanism and lightweight modules while optimizing the loss function, thereby improving floral feature extraction capabilities and reducing computational complexity. …”
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Detection method of small size defects on pipeline weld surface based on improved YOLOv7. by Xiangqian Xu, Wenting Hou, Xing Li

“…Then, the convolution module in the backbone network and the feature fusion network is replaced by the depthwise separable convolution with less computational overhead, so as to effectively reduce the network calculation, parameter quantity and model volume. …”
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Recursive-Parallel Algorithm for Solving the Maximum Common Subgraph Problem by Vladimir V. Vasilchikov

“…For the experiment, the author developed a special application in the C# language designed to generate various sets of initial data with specified parameters. The paper describes the features of the generated initial pairs of graphs, as well as the results obtained during the experiment.…”
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Broiler Behavior Detection and Tracking Method Based on Lightweight Transformer by Haixia Qi, Zihong Chen, Guangsheng Liang, Riyao Chen, Jinzhuo Jiang, Xiwen Luo

“…In addition, we propose a new cross-scale feature fusion network to optimize the neck network of the original model. …”
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E-MobileViT: a lightweight model for traffic sign recognition by Shiqi Song, Xinfeng Ye, Sathiamoorthy Manoharan

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Forced Convection Heat Transfer in V-Pattern Folded Core Sandwich Structures by Sifeng Li, Zhijin Wang, Chen Zhou

“…Based on the periodic feature of folded core, a methodology to simulate the fully developed flow and heat transfer state with a few unit cells is developed. …”
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SBCS-Net: Sparse Bayesian and Deep Learning Framework for Compressed Sensing in Sensor Networks by Xianwei Gao, Xiang Yao, Bi Chen, Honghao Zhang

“…The core of SBCS-Net is to optimize key SBL parameters through end-to-end learning. This can adaptively improve signal sparsity and probabilistically process measurement noise, while fully leveraging the powerful feature extraction and global context modeling capabilities of deep learning modules. …”
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