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

“…Two versions of the adaptive mesh-size algorithm are studied, optimized for either best quality or balanced performance and computation cost. …”
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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.…”
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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. …”
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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.…”
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Peri-operative intrastromal corneal segmentation after creation of corneal cuts based on laser induced optical breakdown: A perspective study by Mehrjoo Masoud, Pacuraru Alexander, Krüger Luise, Beck Florian, Doll Konrad, Mosquera Samuel Arba

“…This study introduces an automated image processing algorithm that integrates non-local denoising, the Sobel gradient method, and Bayesian optimization to accurately delineate lenticule volumes and flap surfaces. …”
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Optimasi Algoritma Naive Bayes dengan Diskritisasi K-Means pada Diagnosis Penyakit Jantung by Nafa Fajriati, Budi Prasetiyo

“…This shows that K-means discretization plays a role in optimizing the performance of the Naïve Bayes algorithm to produce better accuracy. …”
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A Study on the Impact of Obstacle Size on Training Models Based on DQN and DDQN by Lu Siyu, Tao Ye, Zeng Junwei, Zuo Qihuan

“…Various parameters such as obstacle size and complexity influence the agent's performance, promoting efficient learning and policy optimization using both DQN and DDQN algorithms under different configurations. …”
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Unsupervised Image Classification Based on Fully Fuzzy Voronoi Tessellation by Xiaoli Li, Longlong Zhao, Hongzhong Li, Luyi Sun, Pan Chen, Ruixia Jiang, Jinsong Chen

“…It greatly increases the convergence speed of the algorithm. Experiments have been performed on simulated and several remote sensing images with seven comparing algorithms to demonstrate the effectiveness of the proposed algorithm.…”
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rhBNN+ Comprehensive Detections and Analyses of the Human Body Temperatures and Sounds by the Same Smart Mask by Bingcan Liao, Pin Sun, Shuyi Chen, Rihong Huang, Junyu Yang, Guofeng Li, Chengzhi Lv, Nan Zhu, Shui Guan, Hailong Liu, Rong Liu, Ali Mansouri, Changkai Sun

“…The SVM achieved 84.3% accuracy for sound data classification, while the Lion algorithm−optimized SVM achieved an even higher accuracy of 93.6%. …”
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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. …”
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Investigation on Circadian Action and Color Quality in Laser-Based Illuminant for General Lighting and Display by Shuo-Di Lei, Bi-Jing Liu, Yang Gao, Xiao-Ya Dong, Yu-Jia Gong, Jian Xu, Yun-Xin Xu, Dong Wang, Zi-Quan Guo, Ting-Zhu Wu, Chen-Liang Zhou, Zong-Jian Cai, Yi-Jun Lu, Zhong Chen

“…In this work, the genetic algorithm is employed to optimize both circadian action factor (CAF) and color quality of laser-based illuminants (LBIs) with three, four, and five spectral bands to disclose its possible use in two common white lighting applications, i.e. bedroom lighting and office lighting. …”
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Heterogeneous Multi-Agent Deep Reinforcement Learning for Cluster-Based Spectrum Sharing in UAV Swarms by Xiaomin Liao, Yulai Wang, Yang Han, You Li, Chushan Lin, Xuan Zhu

“…Each UAV is equipped with an intelligent agent to execute the deep reinforcement learning (DRL) algorithm. Correspondingly, the HMDRL-UC consists of two parts: multi-agent proximal policy optimization for cluster head (MAPPO-H) and independent proximal policy optimization for cluster member (IPPO-M). …”
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Photovoltaic Power Forecasting with Weather Conditioned Attention Mechanism by Xuetao Jiang, Yuchun Gou, Meiyu Jiang, Lihui Luo, Qingguo Zhou

“…We propose a Multi-Stream Attention Fusion Network (MSAFN) which utilizes an algorithm to derive the optimal decomposition algorithm for different weather conditions. …”
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Robust Beamforming for Superdirective Antenna Arrays and Experimental Validations by Mengying Gao, Haifan Yin, Liangcheng Han, Jingcheng Xie

“…To solve this optimization problem, we propose an efficient orthogonal complement-aided quadratic constraint least squares (OC-QCLS) algorithm, which achieves the maximum possible directivity under the sensitivity constraint. …”
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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. …”
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Capacity Estimation and Knee Point Prediction Using Electrochemical Impedance Spectroscopy for Lithium Metal Battery Degradation via Machine Learning by Qianli Si, Shoichi Matsuda, Yasunobu Ando, Toshiyuki Momma, Yoshitaka Tateyama

“…To reduce data complexity and improve model efficiency, the input by selecting specific frequency points based on SHAP values is further optimized. The optimized models exhibit comparable or improved accuracy compared to those using the whole EIS data and have reasonable performance on unseen test data. …”
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Scalable FPGA Implementation of a Reliability-Based Direct Turbo Decoder for Short Block Codes by Senthil Murugan, Ramesh Bhakthavatchalu, Karthi Balasubramanian, B. Yamuna, Deepak Mishra, Sree Ranjani Rajendran

“…This paper presents the first hardware implementation of the RCODD algorithm on an FPGA, featuring a serial architecture optimized for minimal memory usage and logic complexity. …”
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