LEAF-YOLO: Lightweight Edge-Real-Time Small Object Detection on Aerial Imagery by Van Quang Nghiem, Huy Hoang Nguyen, Minh Son Hoang

“…LEAF-YOLO-N achieves 21.9% AP.50:.95 and 39.7% AP.50 with only 1.2M parameters. LEAF-YOLO achieves 28.2% AP.50:.95 and 48.3% AP.50 with 4.28M parameters. …”
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Context-Adaptable Deployment of FastSLAM 2.0 on Graphic Processing Unit with Unknown Data Association by Jessica Giovagnola, Manuel Pegalajar Cuéllar, Diego Pedro Morales Santos

“…The parallelization process involves identifying the parameters affecting the computational complexity in order to distribute the computation among single multiprocessors as efficiently as possible. …”
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Cross-Modal Data Fusion via Vision-Language Model for Crop Disease Recognition by Wenjie Liu, Guoqing Wu, Han Wang, Fuji Ren

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RP-DETR: end-to-end rice pests detection using a transformer by Jinsheng Wang, Tao Wang, Qin Xu, Lu Gao, Guosong Gu, Liangquan Jia, Chong Yao

“…In this regard, the paper introduces an effective rice pest detection framework utilizing the Transformer architecture, designed to capture long-range features. The paper enhances the original model by adding the self-developed RepPConv-block to reduce the problem of information redundancy in feature extraction in the model backbone and to a certain extent reduce the model parameters. …”
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Explainable Machine Learning and Predictive Statistics for Sustainable Photovoltaic Power Prediction on Areal Meteorological Variables by Sajjad Nematzadeh, Vedat Esen

“…The resulting subset, dominated by apparent temperature and diffuse, direct, global-tilted, and terrestrial irradiance, reduces dimensionality without significantly degrading accuracy. Feature importance is then quantified through two complementary aspects: (a) tree-based permutation scores extracted from a set of ensemble models and (b) information gain computed over random feature combinations. …”
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Deep Learning Model for Analyzing EEG Signal Analysis by Varun Gupta, Vivek Kumar, Prince, Saurabh Singh, Young-Seok Lee, In-Ho Ra

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GDFC-YOLO: An Efficient Perception Detection Model for Precise Wheat Disease Recognition by Jiawei Qian, Chenxu Dai, Zhanlin Ji, Jinyun Liu

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A lightweight algorithm for steel surface defect detection using improved YOLOv8 by Shuangbao Ma, Xin Zhao, Li Wan, Yapeng Zhang, Hongliang Gao

“…Firstly, GhostNet is utilized as the backbone network in order to reduce the number of model parameters and computational complexity. Secondly, the MPCA (MultiPath Coordinate Attention) attention mechanism is integrated to enhance feature extraction capabilities. …”
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The Development of a Lightweight DE-YOLO Model for Detecting Impurities and Broken Rice Grains by Zhenwei Liang, Xingyue Xu, Deyong Yang, Yanbin Liu

“…Firstly, changing the CBS module to the DBS module in the entire network model and replacing the standard convolution with Depthwise Separable Convolution (DSConv) can effectively reduce the number of parameters and the computational complexity, making the model lightweight. …”
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Infrared object detection for robot vision based on multiple focus diffusion and task interaction alignment by Jixu Zhang, Li Wang, Hung-Wei Li, Meng-Yen Hsieh, Shunxiang Zhang, Hua Wen, Meng Chen

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An improved lightweight method based on EfficientNet for birdsong recognition by Haolun He, Hui Luo

“…The proposed method introduces the ECA attention mechanism to reduce the parameter complexity while improving feature expression. …”
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An improved method of AUD-YOLO for surface damage detection of wind turbine blades by Li Zou, Anqi Chen, Xinhua Yang, Yibo Sun

“…Firstly, the ADown module is integrated into the YOLOv8 backbone to replace some conventional convolutional down-sampling operations, decreasing the parameter count while boosting the model’s capability to extract image features. …”
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LSD-Det: A Lightweight Detector for Small Ship Targets in SAR Images by Zhen Wang, Bin Qin, Shang Gao

“…Additionally, a Global-Enhanced Dilated Wavelet Transform (GEDWT) module is embedded in the neck’s C2f structure to enhance multi-scale feature representation with minimal computational overhead. …”
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RGE-YOLO enables lightweight road packaging bag detection for enhanced driving safety by Dangfeng Pang, Zhiwei Guan, Tao Luo, Yanhao Liang, Ruzhen Dou

“…GSConv reduces redundant computations, enhancing model lightweight; EMA enhances the model’s ability to capture multi-scale information by integrating channel and spatial attention mechanisms; RepViTBlock integrates convolution and self-attention mechanisms to improve feature extraction capabilities. …”
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YOLORM: An Advanced Key Point Detection Method for Accurate and Efficient Rotameter Reading in Low Flow Environments by Huang Yong, Xia Xing, Xiao Shengwang

“…Notably, compared to Hourglass, HRNet, and HigherHRNet, YOLORM reduced parameters by 99.3%, 92.9%, and 96.8%, and computational cost by 98.8%, 90.2%, and 95.3%, respectively, while concurrently improving precision and recall. …”
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DualCascadeTSF-MobileNetV2: A Lightweight Violence Behavior Recognition Model by Yuang Chen, Yong Li, Shaohua Li, Shuhan Lv, Fang Lin

“…Meanwhile, the model incorporates the efficient lightweight structure of MobileNetV2, significantly reducing the number of parameters and computational complexity. Experiments were conducted on three public violent behavior datasets, Crowd Violence, RWF-2000, and Hockey Fights, to verify the performance of the model. …”
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Efficient Wheat Disease Identification Using Hybrid Swin-SHARP Vision Model by Waqar Khalid, Yazeed Alkharijah, Syed Muhammad Usman, Shehzad Khalid

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YOLOv8-RBean: Runner Bean Leaf Disease Detection Model Based on YOLOv8 by Hongbing Chen, Haoting Zhai, Jinghuan Hu, Hongrui Chen, Changji Wen, Yizhe Feng, Kun Wang, Zhipeng Li, Guangyao Wang

“…Moreover, the model reduces the number of parameters to 2.71 M and computational cost to 7.5 GFLOPs, representing reductions of 10% and 7.4% compared to the baseline model. …”
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Optimized Negative Selection Algorithm for Image Classification in Multimodal Biometric System by Monsurat Omolara Balogun, Latifat Adeola Odeniyi, Elijah Olusola Omidiora, Stephen Olatunde Olabiyisi, Adeleye Samuel Falohun

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Fast forward modeling and response analysis of extra-deep azimuthal resistivity measurements in complex model by Pan Zhang, Shaogui Deng, Xiyong Yuan, Fen Liu, Weibiao Xie

“…During the geosteering process, fault and wedge models were simulated, and various feature parameters were extracted to assess their impact on the simulation outcomes of EDARM. …”
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