DHQ-DETR: Distributed and High-Quality Object Query for Enhanced Dense Detection in Remote Sensing by Chenglong Li, Jianwei Zhang, Bihan Huo, Yingjian Xue

“…With the widespread application of remote sensing technologies and UAV imagery in various fields, dense object detection has become a significant and challenging task in computer vision research. Existing end-to-end detection models, particularly those based on DETR, often face criticism due to their high computational demands, slow convergence rates, and inadequacy in managing dense, multi-scale objects. …”
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A robust method for calculating the vertical derivative of potential fields based on Hilbert transforms by Xin’gang Luo, Shengrong Liu, Xiaoping Tang

“…Conventional methods for obtaining these derivatives often face stability limitations, particularly when computing higher-order derivatives. …”
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sEMG-based gesture recognition using multi-stream adaptive CNNs with integrated residual modules by Yutong Xia, Dawei Qiu, Cheng Zhang, Jing Liu

“…In the future, in order to deal with differences in sEMG signals caused by variations among individuals, a universal multi-gesture recognition algorithm should be developed. Meanwhile, the model should focus on optimizing and streamlining the network to reduce computational load.…”
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A seismic random noise suppression method based on CNN-Mamba by Xiujuan WEI, Xingye LIU, Huailai ZHOU

“…The hardware-aware parallel algorithm of Mamba was employed to reduce the computational resource consumption, thus ensuring the denoising performance while enhancing computational efficiency. …”
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Simulation-based deep reinforcement learning for multi-objective identical parallel machine scheduling problem by Sohyun Nam, Young-in Cho, Jong Hun Woo

“…However, due to the extensive computational time, these methods face limitations in addressing short-term scheduling problems for the unit production systems of shipbuilding processes, where various environmental uncertainties must be considered. …”
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Precision autofocus in optical microscopy with liquid lenses controlled by deep reinforcement learning by Jing Zhang, Yong-feng Fu, Hao Shen, Quan Liu, Li-ning Sun, Li-guo Chen

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Atmospheric Modeling for Wildfire Prediction by Fathima Nuzla Ismail, Brendon J. Woodford, Sherlock A. Licorish

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Robust GNSS/INS Tightly Coupled Positioning Using Factor Graph Optimization with P-Spline and Dynamic Prediction by Bokun Ning, Fang Zhao, Haiyong Luo, Dan Luo, Wenhua Shao

“…The combination of GNSS RTK and INS offers complementary advantages but faces significant challenges in urban canyons. Frequent cycle slips in carrier phase measurements and ambiguity resolution algorithms increase computational burden without improving positioning accuracy. …”
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High-Precision Positioning Method for Robot Acoustic Ranging Based on Self-Optimization of Base Stations by Zekai Zhang, Jiayu Chen, Bishu Gao, Yefeng Sun, Xiaofeng Ling, Zheyuan Li, Liang Gong

“…Currently, time-of-flight (TOF)-based acoustic ranging positioning systems face challenges such as the susceptibility of sound velocity to environmental factors and the loss of acoustic signals at both short and long distances, which leads to a reduction in positioning accuracy. …”
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Analysis of State-of-Charge Estimation Methods for Li-Ion Batteries Considering Wide Temperature Range by Yu Miao, Yang Gao, Xinyue Liu, Yuan Liang, Lin Liu

“…However, it requires high-quality data and substantial computational resources. Future research should focus on developing high-precision, temperature-adaptive models and lightweight real-time algorithms. …”
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Efficient vision transformers with edge enhancement for robust small target detection in drone-based remote sensing by Xuguang Zhu, Zhizhao Zhang

“…Small object detection in UAV remote sensing imagery faces significant challenges due to scale variations, background clutter, and real-time processing requirements. …”
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GE-YOLO for Weed Detection in Rice Paddy Fields by Zimeng Chen, Baifan Chen, Yi Huang, Zeshun Zhou

“…Additionally, an EMA attention mechanism is used to better learn weed feature representations, while a GIOU loss function provides smoother gradients and reduces computational complexity. Multiple experiments demonstrate that GE-YOLO achieves 93.1% mAP, 90.3% F1 Score, and 85.9 FPS, surpassing almost all mainstream object detection algorithms such as YOLOv8, YOLOv10, and YOLOv11 in terms of detection accuracy and overall performance. …”
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Hybrid multi-objective node deployment for energy-coverage problem in mobile underwater wireless sensor networks by Salmah Fattah, Ismail Ahmedy, Mohd Yamani Idna Idris, Abdullah Gani

“…The proposed solution introduced a hybrid adaptive multi-parent crossover genetic algorithm and fuzzy dominance-based decomposition approach by adapting the original non-dominated sorting genetic algorithm II. …”
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Enhanced water saturation estimation in hydrocarbon reservoirs using machine learning by Ali Akbari, Ali Ranjbar, Yousef Kazemzadeh, Dmitriy A. Martyushev

“…Nine well log parameters—Depth (DEPT), High-Temperature Neutron Porosity, True Resistivity, Computed Gamma Ray, Spectral Gamma Ray, Hole Caliper, Compressional Sonic Travel Time, Bulk Density, and Temperature—were used as input features to train and test five ML algorithms: Linear Regression, Support Vector Machine (SVM), Random Forest, Least Squares Boosting, and Bayesian methods. …”
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Classification of English Words into Grammatical Notations Using Deep Learning Technique by Muhammad Imran, Sajjad Hussain Qureshi, Abrar Hussain Qureshi, Norah Almusharraf

“…The classification of parts of speech into different grammatical notations is the major problem that non-native English learners face. This situation stresses the need to develop a computer-based system using a machine learning algorithm to classify words into proper grammatical notations. …”
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Detection of kidney bean leaf spot disease based on a hybrid deep learning model by Yiwei Wang, Qianyu Wang, Yue Su, Binghan Jing, Meichen Feng

“…However, traditional machine learning methods face limitations in feature extraction, while deep learning approaches, despite their advantages, are computationally expensive and do not always yield optimal results. …”
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Aircraft Multi-stage Altitude Prediction Under Satellite Signal Loss by Mengchan HUANG, Qiang MIAO

“…Compared to RNNs and their variants, the LTCA–TCN algorithm yields superior prediction results while maintaining a simpler structure and requiring fewer computational resources. …”
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Applied Machine Learning to Anomaly Detection in Enterprise Purchase Processes: A Hybrid Approach Using Clustering and Isolation Forest by Antonio Herreros-Martínez, Rafael Magdalena-Benedicto, Joan Vila-Francés, Antonio José Serrano-López, Sonia Pérez-Díaz, José Javier Martínez-Herráiz

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Multi-risk-scenarios flexibility evaluation model of regional power grid considering economic efficiency of dispatching measures by ZHOU Qihang, GUAN Lin, XIAN Weihong, XUAN Peizheng, CHENG Lanfen, LI Zixi

“…The test results indicate that the proposed indicators, models, and algorithm can reflect the requirements and capabilities of regional power grids for operational flexibility with consideration of rich risk scenarios. …”
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Towards Efficiency and Endurance: Energy–Aerodynamic Co-Optimization for Solar-Powered Micro Air Vehicles by Weicheng Di, Xin Dong, Zixing Wei, Haoji Liu, Zhan Tu, Daochun Li, Jinwu Xiang

“…To address this, this work proposes an automated algorithm for optimal solar panel arrangement on complex upper surfaces of the MAV. …”
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