Apple Pest and Disease Detection Network with Partial Multi-Scale Feature Extraction and Efficient Hierarchical Feature Fusion by Weihao Bao, Fuquan Zhang

“…To address this issue, this study proposes an improved pest and disease detection algorithm, YOLO-PEL, based on YOLOv11, which integrates multiple innovative modules, including PMFEM, EHFPN, and LKAP, combined with data augmentation strategies, significantly improving detection accuracy and efficiency in complex environments. …”
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Field Trial Transmission of Time Frequency Packed DP-QPSK Superchannel With Spectral Efficiency of 6.2 bit/s/Hz by Gianluca Meloni

“…The use of low-order modulation format guarantees better robustness in terms of optical-signal-to-noise ratio (OSNR) and reduced complexity with respect to higher order formats. At the receiver side, coherent detection was used, together with iterative maximum <bold> <italic>a posteriori</italic></bold> probability (MAP) detection and decoding. …”
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Non-orthogonal Discrete Multi-tone With Low Decoding Complexity Utilizing Symmetric Compression in Time&#x2013;Frequency Space by Pengcheng Wei, Qi Sui, Zibin Li, Fan Li, Xingwen Yi, Zhaohui Li

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Research on a Visually Assisted Efficient Blind-Guiding System and an Autonomous Shopping Guidance Robot Arm Adapted to the Complex Environment of Farmers’ Markets by Mei Liu, Yunhua Chen, Jinjun Rao, Wojciech Giernacki, Zhiming Wang, Jinbo Chen

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An FPGA Prototype for Parkinson&#x2019;s Disease Detection Using Machine Learning on Voice Signal by Mujeev Khan, Abdul Moiz, Gani Nawaz Khan, Mohd Wajid, Mohammed Usman, Jabir Ali

“…This paper proposes an efficient machine learning model for PD detection using voice-based features, which offer a non-invasive, cost-effective, and accessible alternative to complex imaging methods. …”
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Robust Miner Detection in Challenging Underground Environments: An Improved YOLOv11 Approach by Yadong Li, Hui Yan, Dan Li, Hongdong Wang

“…The Efficient Channel Attention (ECA) mechanism was integrated into the YOLOv11 model to enhance the model’s ability to focus on key features, thereby significantly improving detection accuracy. …”
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Ensemble deep learning and anomaly detection framework for automatic audio classification: Insights into deer vocalizations by Salem Ibrahim Salem, Sakae Shirayama, Sho Shimazaki, Kazuo Oki

“…This segmentation method relies on acoustic anomaly detection and can markedly improve computational efficiency, facilitating deployment in environments with limited resources. …”
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A hybrid deep learning model EfficientNet with GRU for breast cancer detection from histopathology images by M. Pradeepa, B. Sharmila, M. Nirmala

“…Abstract Breast cancer remains a significant global health challenge among women, with histopathological image analysis playing a critical role in early detection. However, existing diagnostic models often struggle to extract complex patterns from high-resolution tissue images, limiting their diagnostic accuracy and generalization. …”
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Utilizing an Enhanced YOLOv8 Model for Fishery Detection by Hanyu Jiang, Jiacheng Zhong, Fuyu Ma, Cheng Wang, Ruiwen Yi

“…The results demonstrate that our method provides an efficient and reliable automatic detection technology for precision underwater fishing.…”
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Hardware and Software Complex for the Study of the Joint Use of Technical Means Based on Various Physical Principles by E. I. Mikhnionok, A. V. Khizniak

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A novel edge crop method and enhanced YOLOv5 for efficient wind turbine blade damage detection by Boyu Feng, Bo Liu, Li Song, Yongyan Chen, Xiaofeng Jiao, Baiqiang Wang

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A machine learning-based efficient anomaly detection system for enhanced security in compromised and maligned IoT Networks by Anita Punia, Manish Tiwari, Sourabh Singh Verma

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An Efficient Weed Detection Method Using Latent Diffusion Transformer for Enhanced Agricultural Image Analysis and Mobile Deployment by Yuzhuo Cui, Yingqiu Yang, Yuqing Xia, Yan Li, Zhaoxi Feng, Shiya Liu, Guangqi Yuan, Chunli Lv

“…This paper presents an efficient weed detection method based on the latent diffusion transformer, aimed at enhancing the accuracy and applicability of agricultural image analysis. …”
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SPDC-YOLO: An Efficient Small Target Detection Network Based on Improved YOLOv8 for Drone Aerial Image by Jingxin Bi, Keda Li, Xiangyue Zheng, Gang Zhang, Tao Lei

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Efficient Vehicle Detection and Optimization in Multi-Graph Mode Considering Multi-Section Tracking Based on Geographic Similarity by Yue Chen, Jian Lu

“…At present, complex deep learning algorithms are often used for vehicle detection and tracking, but high-precision detection results are often obtained at the cost of time, and the existing research rarely considers optimization algorithms for vehicle information. …”
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Assessing the Sensitivity and Efficiency of Laser-Induced Breakdown Spectroscopy (LIBS) for High-Concentration Cadmium Detection in Cocoa Powder by Juan Molina M., Raquel Pincay, Víctor Santos, José Luis González, María Fernanda Trujillo Guerrero, Diego Díaz Pace, César Costa-Vera

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DualPFL: A Dual Sparse Pruning Method with Efficient Federated Learning for Edge-Based Object Detection by Shijin Song, Sen Du, Yuefeng Song, Yongxin Zhu

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MoSViT: a lightweight vision transformer framework for efficient disease detection via precision attention mechanism by Yuanqi Chen, Aiping Wang, Ziyang Liu, Jie Yue, Enxu Zhang, Fei Li, Ning Zhang

“…These results surpass leading models such as Swin Transformer V2, DenseNet121, and EfficientNet V2 in both accuracy and parameter efficiency. …”
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Pod-pose : an efficient top-down keypoint detection model for fine-grained pod phenotyping in mature soybean by Fei Liu, Hang Liu, Qiong Wu, Zhongzhi Han, Shanchen Pang, Shudong Wang, Longgang Zhao

“…Specifically, Pod-pose integrates the architectural strengths of various advanced YOLO (You Only Look Once) models through bottleneck structure optimization and positional feature enhancement to achieve superior detection accuracy. Furthermore, we implemented a two-stage detection method augmented with transfer learning, which not only reduces training complexity but also significantly enhances the model's performance. …”
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Enhancing wind turbine blade damage detection with YOLO-Wind by Zhao Zhanfang, Li Tuo

“…The architecture replaces standard convolutions with depthwise separable convolutions (DWConv) to optimize computational efficiency without compromising detection accuracy. …”
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