An adaptive continuous threshold wavelet denoising method for LiDAR echo signal by Dezhi Zheng, Tianchi Qu, Chun Hu, Shijia Lu, Zhongxiang Li, Guanyu Yang, Xiaojun Yang

“…The adaptive threshold is dynamically adjusted according to the wavelet decomposition level, and the continuous threshold function ensures continuity with lower constant error, thus optimizing the denoising process. Simulation results show that the proposed algorithm has excellent performance in improving SNR and reducing root mean square error (RMSE) compared with other algorithms. …”
Get full text

Closely Spaced Multi-Target Association and Localization Using BR and AOA Measurements in Distributed MIMO Radar Systems by Zehua Yu, Ziyang Jin, Ting Sun, Jinshan Ding, Jun Li, Qinghua Guo

“…The message-passing algorithm dynamically approximates the complex local functions involved in the problem, delivering excellent performance while maintaining low complexity. …”
Get full text

ADAM-DETR: an intelligent rice disease detection method based on adaptive multi-scale feature fusion by Hanyu Song, Xinyue Huang, Ziqiang Wang, Jianwei Hu, Huasheng Zhang, Hui Yang

“…Experimental results demonstrate that ADAM-DETR achieves 94.76% mAP@50 on the RiDDET-5 dataset, representing a 3.25% improvement over the baseline, and 83.32% mAP@50 on the public Kamatis dataset with a 2.19% enhancement, validating its cross-domain generalization capability. The algorithm requires only 42.8G FLOPs with 14.3M parameters, achieving an optimal balance between accuracy and efficiency, providing an effective technical solution for disease monitoring in smart agriculture.…”
Get full text

Sensitive and specific peak detection for SELDI-TOF mass spectrometry using a wavelet/neural-network based approach. by Vincent A Emanuele, Gitika Panicker, Brian M Gurbaxani, Jin-Mann S Lin, Elizabeth R Unger

“…The wavelet denoising part of the algorithm optimally smoothes the signal in each spectrum according to an improved suite of signal processing algorithms previously reported (the LibSELDI toolbox under development). …”
Get full text

Investigating Motion Data Selections Based on Patient-Specific Respiration Pattern at External Surrogates Radiotherapy Using Cyberknife Synchrony Respiratory Tracking System by Seyed Amirreza Dastyar, Ahmad Esmaili Torshabi

“…As example, for a patient with high motion variability while the number of critical data points recognized by our algorithm is significant, the targeting error with and without utilizing these data points are 4.4 mm and 6.6 mm, respectively. …”
Get full text

IMU-aided adaptive mesh-grid based video motion deblurring by Ahmet Arslan, Gokhan Koray Gultekin, Afsar Saranli

“…Motion blur is a problem that degrades the visual quality of images for human perception and also challenges computer vision tasks. While existing studies mostly focus on deblurring algorithms to remove uniform blur due to their computational efficiency, such approaches fail when faced with non-uniform blur. …”
Get full text

Improved stereo matching network based on dense multi-scale feature guided cost aggregation by ZHANG Bo, ZHANG Meiling, LI Xue, ZHU Lei

“…Compared with existing stereo matching algorithms such as GWCNet and CPOP-Net, the proposed algorithm performs well in the ill-posed regions.…”
Get full text

Deep learning-based semantic segmentation with novel navigation line extraction for autonomous agricultural robots by Chijioke Leonard Nkwocha, Ning Wang

“…The results of the experiments showed that PSPNet achieved the highest mean intersection over union (mIoU) of 96.50%, followed by Deeplabv3+ (96.30%) and ENet (95.13%). While ENet showed more consistent performance across various lighting conditions, the novel algorithm demonstrated remarkable accuracy, reducing angle errors to an average of 1.1°, 1.6°, and 1.6° for ENet, Deeplabv3+, and PSPNet, respectively, compared to 4.6°, 4.9°, and 6.7° using the baseline method. …”
Get full text

A longan-picking sequence planning method for UAV system based on multi-target tracking by Kaixuan Wu, Meiqi Zhang, Linlin Shi, Hengxu Chen, Yuju Mai, Mingda Luo, Hengyi Lin, Jun Li

“…A comparative analysis shows that the proposed method achieves an average improvement of 71. 7% in silhouette coefficient, a 67% reduction in the average distance within the cluster and a 30. 1% increase in the average distance between groups, allowing effective subdivision of subareas of picking. A LonTsp planning algorithm is used for path planning, optimizing picking paths to reduce total picking time by 19.1% and lowering UAV energy consumption and time costs. …”
Get full text

A Novel Transformer-Based Approach for Reliability Evaluation of Composite Systems With Renewables and Plug-in Hybrid Electric Vehicles by Chiranjeevi Yarramsetty, Tukaram Moger, Debashisha Jena, Veeranki Srinivasa Rao

“…To address these issues, this research presents an advanced mixed-integer linear programming (MILP)-based algorithm for optimizing EV charging. The algorithm prioritizes clean energy utilization through intelligent power allocation strategies while considering cost-revenue trade-offs. …”
Get full text

Energy-efficient power control for two-tier femtocell networks with block-fading channels by Zhixin Liu, Jieshuai Wu, Yang Liu, Hongjiu Yang, Jianfeng Guan, Yu Wang

“…A distributed iterative algorithm is proposed to obtain the optimal power solution. …”
Get full text

ROITP: Road Obstacle-Involved Trajectory Planner for Autonomous Trucks by Yechen Qin, Yiwei Huang, Wenhao Yu, Hong Wang

“…The planner categorizes road obstacles using a learning-based algorithm. A discrete optimization algorithm selects a multi-objective optimal trajectory while taking into account constraints and objective functions derived from truck dynamics. …”
Get full text

Application of the Mean-shift Segmentation Parameters Estimator (MSPE) to VHSR satellite images: Tetuan-Morocco by O. Benarchid, N. Raissouni, J.A. Sobrino, A. El Ayyan

“…<p>Image segmentation is considered as crucial step dealing with Object-Based Image Analysis (OBIA) and different segmentation results could be achieved by combining possible parameters values. Optimal parameters selection is usually carried out on the basis of visual interpretation; therefore, defining optimal combinations is a challenging task. …”
Get full text

Improving inverter efficiency for electric vehicles: Experimental validation of the neural network-based SHE technique using RT-LAB by Seyf Eddine Bechekir, Mokhtaria Jbilou, Mostefa Brahami, Fatima Zohra Boudjella, Imen Souhila Bousmaha, Mimouna Oukli, Said Nemmich

“…MATLAB/Simulink simulations and experimental results on the RT-LAB simulator confirm the algorithm’s capability to calculate optimal switching angles and produce high-performance PWM waveforms. …”
Get full text

Implementation of VR application in cultural and tourism integration under the background of smart city and IoT by Wei Huang

“…In terms of system performance, the optimized virtual roaming system maintained stable memory and CPU usage while reducing GPU load by over 20 % and increasing the FPS from 30 fps to 44.6 fps. …”
Get full text

UAV Robust Strategy Control Based on MAS by Jian Han, Changhong Wang, Guoxing Yi

“…After simulation, the MAS has been proved to be able to promote the success ratio and raise the robustness, while realizing feasibility of coordinated flight and optimality of cooperative mission.…”
Get full text

Probabilistic alignment of multiple networks by Teresa Lázaro, Roger Guimerà, Marta Sales-Pardo

“…Our approach opens the door to a whole new family of network alignment algorithms, and to their application to problems for which existing methods are perhaps inappropriate.…”
Get full text

Fingerprint Classification Based on Multilayer Extreme Learning Machines by Axel Quinteros, David Zabala-Blanco

“…A brute-force heuristic optimization approach is applied to determine the hyperparameters that maximize classification accuracy across different M-ELM configurations while avoiding excessive training times. …”
Get full text

Application of LiDAR and SLAM Technologies in Autonomous Systems for Precision Grapevine Pruning and Harvesting by Obaid Saif, Mohammed G., Nagaraju Krishna Chythanya

“…The project aims to integrate advanced technologies in grapevine pruning and harvesting to optimize these processes. The system improves accuracy and speed, reducing labor costs while enhancing grape yield and quality, representing a promising approach to vineyard management. …”
Get full text

Fast Low Rank and Sparse Decomposition Based on Greedy Bilateral Smoothing for Infrared Small Target Detection by Yan-Shan Zhang, Ze-Yin Li, Dong-Dong Pang, Lu-Yao Wang, Cheng-Jun Wu, Kang Duan, Jun-Ming Gao

“…Then, a optimization algorithm framework based on alternating projection is designed to achieve an accurate separation of target and background. …”
Get full text