Enhancing Tomato Detection in Complex Field Environments using Faster R-CNN Deep Learning Model for Autonomous Picking Robots by Pandey Devras, Lalmawipuii R.

“…However, accurately detecting tomatoes in dynamic and complex field environments remains a challenge due to issues such as high false positive rates, missed detections, variable illumination, occlusion, and heterogeneous foliage. …”
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Efficient removal of lipophilic compounds from sewage sludge: Comparative evaluation of solvent extraction techniques by Basanti Ekka, Inese Mierina, Ruta Zarina, Linda Mezule

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A simulation-driven computational framework for adaptive energy-efficient optimization in machine learning-based intrusion detection systems by Ripal Ranpara, Osamah Alsalman, Om Prakash Kumar, Shobhit K. Patel

“…Abstract This paper presents GreenMU, an innovative proposed novel framework designed to address the two main challenges: energy efficiency as one of the main research components and detection performance in intrusion detection systems. …”
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SP-Pillars: An Efficient LiDAR 3D Objects Detection Framework With Multi-Scale Feature Perception and Optimization by Tingshuai Chen, Ye Yuan, Bingyang Yin, Yuanhong Liao

“…In autonomous driving, achieving rapid detection of target categories and locations is a key technology. …”
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Multi-Scale Fusion Lightweight Target Detection Method for Coal and Gangue Based on EMBS-YOLOv8s by Lin Gao, Pengwei Yu, Hongjuan Dong, Wenjie Wang

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YED-Net: Yoga Exercise Dynamics Monitoring with YOLOv11-ECA-Enhanced Detection and DeepSORT Tracking by Youyu Zhou, Shu Dong, Hao Sheng, Wei Ke

“…Ablation studies confirm that the ECA module, implemented via lightweight 1D convolution, enhances channel attention modeling efficiency by 23% compared to the original SE module and reduces the false detection rate by 1.2 times under complex backgrounds. …”
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A Enhancement the Efficiency of Solar Cell by using Internet of Things Applications by Mohammed Hassan Mjhool, Haider Th. Salim AL Rikabi AL Rikabi, Mansour S. Farhan AL Rikabi

“… Monitoring and maintaining solar cells is one of the most fundamental problems facing investors in Iraq at present. In addition, the efficiency of solar cells is unacceptable because of climate changes. …”
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PVLF: point-voxel local feature fusion for 3D detection by Haowei Zhao, Zhuolei Xiao

“…PVLF explores local spatial features to improve accuracy regarding tiny object detection. To address the potential complex computational issues in the convolution process, we have designed an innovative Adaptive Sparse Convolution (ASC) module that effectively eliminates redundant information in the feature layer. …”
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CHARACTERISTICS OF THE VARIETIES AND LINES OF WINTER WHEAT OBTAINED IN ARRIGC NAMED AFTER I.G. KALINENKO ON RESISTANCE TO A COMPLEX OF PATHOGENS OF ECONOMICALLY VALUABLE DISEASES by G. V. Volkova, O. Yu. Kremneva, Yu. V. Shumilov, Е. V. Sinyak, O. F. Vaganova, E. S. Segeda, D. M. Marchenko, N. E. Samofalova, O. V. Skripka, T. G. Derova

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LiMMCov: An interactive research tool for efficiently selecting covariance structures in linear mixed models using insights from time series analysis. by Perseverence Savieri, Lara Stas, Kurt Barbé

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Polish Farmers′ Perceptions of the Benefits and Risks of Investing in Biogas Plants and the Role of GISs in Site Selection by Anna Kochanek, Józef Ciuła, Mariusz Cembruch-Nowakowski, Tomasz Zacłona

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A Detection Method for Sweet Potato Leaf Spot Disease and Leaf-Eating Pests by Kang Xu, Yan Hou, Wenbin Sun, Dongquan Chen, Danyang Lv, Jiejie Xing, Ranbing Yang

“…This paper proposed an efficient sweet potato leaf disease and pest detection method SPLDPvB, as well as a low-complexity version SPLDPvT, to achieve accurate identification of sweet potato leaf spots and pests, such as hawk moth and wheat moth. …”
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Research on the GST gene family in Salix lindleyana reveals Trp162 and Pro202 as key amino acids controlling the release rate of GS-X by Nan Xu, Yu-Wen Wang, Chang Qu, Zhao-Qun Wu, Xiu-Xing Zhang, Shi-Yi Wang, Ye-Bo Yang, Jing Xue, Hai-Ling Yang

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Pyridine–Quinoline and Biquinoline-Based Ruthenium <i>p</i>-Cymene Complexes as Efficient Catalysts for Transfer Hydrogenation Studies: Synthesis and Structural Characterization by Nikolaos Zacharopoulos, Gregor Schnakenburg, Eleni I. Panagopoulou, Nikolaos S. Thomaidis, Athanassios I. Philippopoulos

“…Searching for new and efficient transfer hydrogenation catalysts, a series of new organometallic ruthenium(II)-arene complexes of the formulae [Ru(η⁶-<i>p</i>-cymene)(L)Cl][PF₆] (<b>1</b>–<b>8</b>) and [Ru(η⁶-<i>p</i>-cymene)(L)Cl][Ru(η⁶-<i>p</i>-cymene)Cl₃] (<b>9</b>–<b>11</b>) were synthesized and fully characterized. …”
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Taylor-Spotted Cat Optimization (Taylor-SCO): An Energy-Efficient Cluster Head Selection Algorithm with Improved Trust Factor for Data Routing in WSN by Shivaraj Kalburgi, M. Manimozhi

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LightMFF: A Simple and Efficient Ultra-Lightweight Multi-Focus Image Fusion Network by Xinzhe Xie, Zijian Lin, Buyu Guo, Shuangyan He, Yanzhen Gu, Yefei Bai, Peiliang Li

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A novel frequency-domain approach to the range migration algorithm for efficient medical image processing: Application in tumor detection and identification by Jaouad El Gueri, Ibtisam Amdaouch, Badiaa Ait Ahmed, Juan Ruiz-Alzola, Otman Aghzout

“…A comprehensive complexity analysis was conducted to evaluate the algorithm’s efficiency and scalability, with a focus on computational time and resource utilization. …”
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Investigating the efficacy of bioactive compounds from selected plant extracts against Gibberella fujikuroi species complex associated with damping off disease in sweet corn by Alyaa Abd Ali, Ayoob Obaid Alfalahi, Aalaa Khudhair Hassan, Ahlam Khalofah, Eilyn Mena, Abdelfattah A. Dababat, Fouad Mokrini

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Efficient Packaging Line Object Counting by Cross-Frame Association With Wavelet Convolutions and Trajectory Compensation by Longxuan Wei, Yutao Zhu, Yufeng Li, Ming Qian, Xiang Zuo, Boan Chen, Shiyu Liang, Zhouhan Lin, Junchi Yan

“…WT-YOLO significantly improves detection accuracy in complex scenes with occlusions and irregular shapes by expanding the receptive field of the network and capturing low-level shape signals, thereby enhancing the network&#x2019;s shape bias. …”
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A novel double machine learning approach for detecting early breast cancer using advanced feature selection and dimensionality reduction techniques by Suganya Athisayamani, Tamilazhagan S, A. Robert Singh, Jae-Yong Hwang, Gyanendra Prasad Joshi

“…This approach effectively captures both structured features and non-linear patterns, making it suitable for datasets with complex dependencies. The second model pairs eXtreme Gradient Boosting (XGBoost), a highly efficient boosting algorithm for tabular data, with an Artificial Neural Network (ANN). …”
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