Improving Balanced Accuracy for Minority Plant Species under Data Imbalance by Ruben Gonzalez-Villanueva, Jose Carranza-Rojas

“…By using self-supervised training together with different sampling algorithms and class weights, we were able to improve the balanced accuracy metric for minority plant species by between 7.9% and 13% without affecting general accuracy. …”
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An Improved Spider Wasp Optimizer for Green Vehicle Route Planning in Flower Collection by Mengxin Lu, Shujuan Wang

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An Improved Constrained Multiobjective Optimization for Energy Multimodal Transport Among Clustering Islands by Xu Yang, Fuxing Zhang, Honglei Miao

“…To address this issue, we develop an unconstrained-individuals guiding constrained multiobjective optimization algorithm, named uiCMOA. Experimental results demonstrate the effectiveness of the transportation network and the efficiency of the proposed algorithm.…”
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Research on downhole drilling target detection based on improved Yolov8n by Jierui Ling, Zhibo Fu, Xinpeng Yuan

“…The results indicate that compared with the original model, the improved model achieves a 14% reduction in model storage size and a 17% decrease in the number of parameters. …”
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Tea Disease Detection Method Based on Improved YOLOv8 in Complex Background by Junchen Ai, Yadong Li, Shengxiang Gao, Rongsheng Hu, Wengang Che

“…Finally, the map values of 89.7% and 68.5% were obtained on a self-made tea data set and a public tea disease data set, which were improved by 3.9% and 4.3%, respectively, compared with the original benchmark model, and the reasoning speed of the model was 164.3 fps. …”
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Evaluation method of hydrophobicity of composite insulators based on improved Mask R-CNN by SHENG Fei, CAO Liu, LIU Yulong, HUANG Jie, HUANG Yaqian, ZHU Yanqing

“…To ensure the safe operation of power system, it is necessary to discriminate the hydrophobicity level online of composite insulators in time. In order to improve the generalization ability of composite insulator hydrophobicity state evaluation model, and solve the problem that the existing classification models only focus on the parts with good hydrophobicity when evaluating the composite insulators with uneven hydrophobicity degree. …”
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Improved Deorientation Processing for Polarimetric SAR Data Using a Phenomenological Approach by Reza Bordbari, Andrew J. Hooper

“…We also demonstrated that, an improved polarimetric target decomposition performance is achieved when the proposed deorientation processing is incorporated into model-based decompositions.…”
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An Optimal Longitudinal Control Strategy of Platoons Using Improved Particle Swarm Optimization by Zhizhou Wu, Zhibo Gao, Wei Hao, Jiaqi Ma

“…Then, a linear-quadratic optimal controller was designed considering the perspectives of driving safety, efficiency, and ride comfort with three performance indicators including vehicle gap error, relative speed, and desired acceleration. An improved particle swarm optimization algorithm was used to optimize the weighting coefficients for the controller state and control variables. …”
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Improved CKD classification based on explainable artificial intelligence with extra trees and BBFS by Ahmed M. Elshewey, Enas Selem, Amira Hassan Abed

“…Also, binary breadth-first search algorithm is used to select the most important features for the proposed explainable artificial intelligence-chronic kidney disease model. …”
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Seedling Stage Corn Line Detection Method Based on Improved YOLOv8 by LI Hongbo, TIAN Xin, RUAN Zhiwen, LIU Shaowen, REN Weiqi, SU Zhongbin, GAO Rui, KONG Qingming

“…[Methods]The proposed method employs machine vision techniques to address common field challenges. YOLOv8-G, an improved object detection algorithm that combines YOLOv8 and GhostNetV2 for lightweight, high-speed performance, was used to detect the central points of crops. …”
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Improvement of Heavy Load Robot Positioning Accuracy by Combining a Model-Based Identification for Geometric Parameters and an Optimized Neural Network for the Compensation of Nong... by Yuxiang Wang, Zhangwei Chen, Hongfei Zu, Xiang Zhang, Chentao Mao, Zhirong Wang

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Research on shale TOC prediction method based on improved BP neural network by Chaorong Wu, Kaixing Huang, Zhengtao Sun, Yizhen Li, Yong Li, Yuexiang Hao, Zhengxing Sun, Ziqi Wang

“…This paper studies a method for predicting shale TOC content using a BP neural network optimized by an improved cuckoo search algorithm. First, for the Longmaxi Formation shale, through logging sensitivity analysis, seven logging parameters sensitive to TOC content were determined: DEN, AC, RT, U, K, GR, and CNL. …”
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DCW-YOLO: An Improved Method for Surface Damage Detection of Wind Turbine Blades by Li Zou, Anqi Chen, Chunzi Li, Xinhua Yang, Yibo Sun

“…This model demonstrates a notable superiority in surface damage detection of WTBs compared to the original YOLOv8n and has achieved a substantial improvement in the mAP@0.5 metric, rising from 91.4% to 93.8%. …”
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YOLO-SRSA: An Improved YOLOv7 Network for the Abnormal Detection of Power Equipment by Wan Zou, Yiping Jiang, Wenlong Liao, Songhai Fan, Yueping Yang, Jin Hou, Hao Tang

“…This paper proposes a YOLO-SRSA-based anomaly detection algorithm. For data enhancement, geometric and color transformations and rain-fog simulations are applied to preprocess the dataset, improving the model’s robustness in outdoor complex weather. …”
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Tomato leaf disease detection method based on improved YOLOv8n by Ming Chen, Chunping Wang, Chengwei Liu, Ying Yu, Yuan Yuan, Jiaxuan Ma, Kaisheng Zhang

“…Compared to traditional loss functions, GIoU performs excellently in handling bounding box overlap and positional accuracy, further improving the model’s detection performance. Experimental results show that the improved model achieves an average precision of 81.8%, precision of 77.1%, and recall of 77.4%. …”
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An Improved Random Forest Approach on GAN-Based Dataset Augmentation for Fog Observation by Yucan Cao, Panpan Zhao, Balin Xu, Jingshu Liang

“…The experiment conducted in Sichuan in February 2024 shows that the improved RF model has achieved an average accuracy of fog density observation of 93%, 6.4% higher than the RF model without data expansion, 3–6% higher than the VGG16, the VGG19, the ResNet50, and the DenseNet169 with or without data expansion. …”
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Leveraging Genomic Annotations and Pleiotropic Enrichment for Improved Replication Rates in Schizophrenia GWAS. by Yunpeng Wang, Wesley K Thompson, Andrew J Schork, Dominic Holland, Chi-Hua Chen, Francesco Bettella, Rahul S Desikan, Wen Li, Aree Witoelar, Verena Zuber, Anna Devor, Bipolar Disorder and Schizophrenia Working Group of the Psychiatric Genomics Consortium, Enhancing Neuro Imaging Genetics through Meta Analysis Consortium, Markus M Nöthen, Marcella Rietschel, Qiang Chen, Thomas Werge, Sven Cichon, Daniel R Weinberger, Srdjan Djurovic, Michael O'Donovan, Peter M Visscher, Ole A Andreassen, Anders M Dale

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An Underwater Velocity-Independent DOA Estimation Based on Improved Toeplitz Matrix Reconstruction by Xuejin Zhao, Zihan Lei, Yu Wang, Gengxin Ning

“…This paper proposes an omnidirectional DOA estimation model based on improved Toeplitz matrix reconstruction to address these issues. …”
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Integration of Structural Characteristics from GEDI Waveforms for Improved Forest Type Classification by Mary M. McClure, Satoshi Tsuyuki, Takuya Hiroshima

“…The highest-performing model was a KNN model with 13 spectral and 3 terrain features achieving 81.7% accuracy. …”
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IPO: An Improved Parrot Optimizer for Global Optimization and Multilayer Perceptron Classification Problems by Fang Li, Congteng Dai, Abdelazim G. Hussien, Rong Zheng

“…The Parrot Optimizer (PO) is a new optimization algorithm based on the behaviors of trained Pyrrhura Molinae parrots. …”
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