An improved multi‐scale YOLOv8 for apple leaf dense lesion detection and recognition by Shixin Huo, Na Duan, Zhizheng Xu

“…Abstract Apple leaf lesions present a challenge for their detection and recognition because of their wide variety of species, morphologies, uneven sizes, and complex backgrounds. …”
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YOLO-SRMX: A Lightweight Model for Real-Time Object Detection on Unmanned Aerial Vehicles by Shimin Weng, Han Wang, Jiashu Wang, Changming Xu, Ende Zhang

“…Unmanned Aerial Vehicles (UAVs) face a significant challenge in balancing high accuracy and high efficiency when performing real-time object detection tasks, especially amidst intricate backgrounds, diverse target scales, and stringent onboard computational resource constraints. …”
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Experimental Analysis of Thermal Performance and Evaluation of Vibration and Utility Function for the Readaptation of a Residential Building in an Experimental Housing Complex by Małgorzata Fedorczak-Cisak, Alicja Kowalska-Koczwara, Piotr Stecz, Anna Shymanska, Davide Ottaviano Palmieri

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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

“…However, research on detecting road packaging bags remains limited, and existing object detection models face challenges in small object detection, computational efficiency, and embedded deployment. …”
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A High-Accuracy Underwater Object Detection Algorithm for Synthetic Aperture Sonar Images by Jiahui Su, Deyin Xu, Lu Qiu, Zhiping Xu, Lixiong Lin, Jiachun Zheng

“…Compared with YOLOv8s, the proposed HAUOD algorithm can achieve <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>6.2</mn><mo>%</mo></mrow></semantics></math></inline-formula> higher accuracy with only <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>50.4</mn><mo>%</mo></mrow></semantics></math></inline-formula> model size, and reduce the computational complexity by half. Moreover, the HAUOD method exhibits significant advantages in balancing computational efficiency and accuracy compared to mainstream detection models.…”
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Classification of SERS spectra for agrochemical detection using a neural network with engineered features by Mateo Frausto-Avila, Monserrat Ochoa-Elias, Jose Pablo Manriquez-Amavizca, María del Carmen González-López, Gonzalo Ramírez-García, Mario Alan Quiroz-Juárez

“…This design ensures computational efficiency by using only dense layers for matrix-vector multiplications. …”
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Infrared Small Target Detection Based on Approximate Background Regularization and Bimodal Slice Based Graph Constraints by Xiaoling Ge, Zipeng Fu, Xuelian Yu, Weixian Qian, Kan Ren, Minjie Wan, Guohua Gu

“…Experimental results show that the proposed method outperforms state-of-the-art approaches in both detection performance and efficiency while demonstrating greater robustness in complex scenarios.…”
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Artificial intelligence for herbicide recommendation: Case study for the use of clomazone in Brazilian soils by Hamurábi Anizio Lins, Matheus de Freitas Souza, Lucrecia Pacheco Batista, Luma Lorena Loureiro da Silva Rodrigues, Francisca Daniele da Silva, Bruno Caio Chaves Fernandes, Stefeson Bezerra de Melo, Paulo Sergio Fernandes das Chagas, Daniel Valadão Silva

“…Its interaction is dependent on the properties of the soil and the herbicide itself and, therefore, is considered complex. An alternative to optimize the use of herbicides is the application of mathematical models to estimate the sorption in the soil, contributing to a more efficient control of weeds and bringing more environmental safety. …”
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MPVF: Multi-Modal 3D Object Detection Algorithm with Pointwise and Voxelwise Fusion by Peicheng Shi, Wenchao Wu, Aixi Yang

“…3D object detection plays a pivotal role in achieving accurate environmental perception, particularly in complex traffic scenarios where single-modal detection methods often fail to meet precision requirements. …”
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Use of Business Intelligence as a Strategic Information Technology in Banking: Farud Discovery & Detection by علی محقر, کارو لوکس, ، فرید حسینی, آصف علی منشی

“…It also explains how BI can be effective technology in industries like banking to overcome critical issue like fraud discovery and detection. The methodology, based on BI, in the form of model named BI model for fraud discovery and detection has been devised and suggested at the end of paper along with it its details for overcoming the above mentioned issue in more effective and efficient manner.…”
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Cotton Leaf Disease Detection Using LLM-Synthetic Data and DEMM-YOLO Model by Lijun Gao, Tiantian Ran, Hua Zou, Huanhuan Wu

“…It plays a crucial role in enhancing cotton yield and quality while promoting the advancement of intelligent agriculture and efficient crop harvesting. This study proposes a novel method for detecting cotton leaf diseases based on large language model (LLM)-generated image synthesis and an improved DEMM-YOLO model, which is enhanced from the YOLOv11 model. …”
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Residual-enhanced graph convolutional networks with hypersphere mapping for anomaly detection in attributed networks by Wasim Khan, Afsaruddin Mohd, Mohammad Suaib, Mohammad Ishrat, Anwar Ahamed Shaikh, Syed Mohd Faisal

“…This study introduces an innovative approach that synergizes the strengths of graph convolutional networks with advanced deep residual learning and a unique residual-based attention mechanism, thereby creating a more nuanced and efficient method for anomaly detection in complex networks. …”
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Enhanced YOLOv5s Model for Improved Multi-Sized Object Detection in Road Scenes by Sangavi Sivanandham, Dharanibai Gunaseelan

“…Detecting objects in complex driving environments is crucial for autonomous vehicles to navigate safely. …”
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Citrus Disease Detection Based on Dilated Reparam Feature Enhancement and Shared Parameter Head by Xu Guo, Xingmeng Wang, Wenhao Zhu, Simon X. Yang, Lepeng Song, Ping Li, Qinzheng Li

“…Current models struggle with accuracy and efficiency due to diverse leaf lesion patterns and complex orchard environments. …”
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Research on the detection of obstacles in front of unmanned vehicles in opencast mines based on binocular vision by Shunling RUAN, Huiguo ZHANG, Qinghua GU, Caiwu LU, Di LIU, Jing MAO

“…The Feffol network model proposed in this paper selects Efficient-v2 as the backbone network structure for feature extraction in the feature extraction stage, selects the Ebifpn feature pyramid module based on the SppCSP structure with SppCSP structure to improve the feature sensing field while enhancing the feature information of different sizes, uses the Focal Loss and CIoU Loss loss functions to balance positive and negative samples, and solve the problem of method failure when there is no intersection between the prediction frame and the real detection frame. …”
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Lane and Traffic Sign Detection for Autonomous Vehicles: Addressing Challenges on Indian Road Conditions by H. S. Gowri Yaamini, Swathi K J, Manohar N, Ajay Kumar G

“…Accurate and precise detection of lanes and traffic signs is predominant for the safety and efficiency of autonomous vehicles and these two significant tasks should be addressed to handle Indian traffic conditions. …”
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Research on a UAV-View Object-Detection Method Based on YOLOv7-Tiny by Yuyang Miao, Xihan Wang, Ning Zhang, Kai Wang, Lianhe Shao, Quanli Gao

“…In addition, introducing the Dilated Weighted Residual (DWR) attention module optimizes the information processing flow, enhancing the algorithm’s ability to capture key information, especially in complex backgrounds. These enhancements collectively enable the model to balance high detection accuracy and computational efficiency, making it well-suited for resource-constrained UAV platforms. …”
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Stochastic Fractal Search for Bayesian Network Structure Learning Under Soft/Hard Constraints by Yinglong Dang, Xiaoguang Gao, Zidong Wang

“…However, the acquisition of expert knowledge faces problems such as excessively high labor costs, limited expert experience, and the inability to solve large-scale and highly complex DAGs. Moreover, the current data learning methods also face the problems of low computational efficiency or decreased accuracy when dealing with large-scale and highly complex DAGs. …”
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Passion Fruit Disease Detection Using Sparse Parallel Attention Mechanism and Optical Sensing by Yajie He, Ningyi Zhang, Xinjin Ge, Siqi Li, Linfeng Yang, Minghao Kong, Yiping Guo, Chunli Lv

“…This study proposes a lightweight deep learning model incorporating a sparse parallel attention mechanism (SPAM) for passion fruit disease detection. Built upon a Convolutional Neural Network (CNN) backbone, the model integrates a dynamically selective attention mechanism to enhance detection performance in cases with complex backgrounds and multi-scale objects. …”
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Research on Target Detection Algorithm for Solder Joint Defects Based on the Improved YOLOv8 by Chengkai Zhang, Xiaocui Feng, Pujun Mao, Fuyan Lv

“…Aiming at the problem of low accuracy in solder joint defect detection caused by the complex background and difficult to extract defect features of circuit boards using through-hole technology (THT), an improved YOLOv8 solder joint defect target detection algorithm was proposed. …”
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