Research on Intrusion Detection Method Based on Transformer and CNN-BiLSTM in Internet of Things by Chunhui Zhang, Jian Li, Naile Wang, Dejun Zhang

“…Traditional Intrusion Detection Systems (IDS) face challenges in handling complex attack types, data imbalance, and feature extraction difficulties in IoT environments. …”
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Real-time detection of Chinese cabbage seedlings in the field based on YOLO11-CGB by Hang Shi, Hang Shi, Changxi Liu, Changxi Liu, Miao Wu, Miao Wu, Hui Zhang, Hui Zhang, Hang Song, Hang Song, Hao Sun, Hao Sun, Yufei Li, Yufei Li, Jun Hu, Jun Hu

“…The model’s outputs are visualized using a heat map, and an Average Temperature Weight (ATW) metric is introduced to quantify the heat map’s effectiveness.Results and discussionComparative analysis reveals that YOLO11-CGB outperforms established object detection models like Faster R-CNN, YOLOv4, YOLOv5, YOLOv8 and the original YOLO11 in detecting Chinese cabbage seedlings across varied heights, angles, and complex settings. …”
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Keypoint Detection and 3D Localization Method for Ridge-Cultivated Strawberry Harvesting Robots by Shuo Dai, Tao Bai, Yunjie Zhao

“…Additionally, incorporating the Gold-YOLO neck structure enhances multi-scale feature fusion, improving detection accuracy and enabling the method to adapt to complex environments. …”
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Fish Detection in Fishways for Hydropower Stations Using Bidirectional Cross-Scale Feature Fusion by Junming Wang, Yuanfeng Gong, Wupeng Deng, Enshun Lu, Xinyu Hu, Daode Zhang

“…This paper proposes a fish detection model for accurate and efficient fish detection. …”
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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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An explainable unsupervised learning approach for anomaly detection on corneal in vivo confocal microscopy images by Ningning Tang, Qi Chen, Yunyu Meng, Daizai Lei, Li Jiang, Yikun Qin, Xiaojia Huang, Fen Tang, Shanshan Huang, Qianqian Lan, Qi Chen, Lijie Huang, Rushi Lan, Xipeng Pan, Huadeng Wang, Fan Xu, Wenjing He

“…BackgroundIn vivo confocal microscopy (IVCM) is a crucial imaging modality for assessing corneal diseases, yet distinguishing pathological features from normal variations remains challenging due to the complex multi-layered corneal structure. Existing anomaly detection methods often struggle to generalize across diverse disease manifestations. …”
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Comprehensive Outlier Detection in Wireless Sensor Network with Fast Optimization Algorithm of Classification Model by Haiqing Yao, Heng Cao, Jin Li

“…Since the nonstationary distribution of the detected objects is general in the real world, the accurate and efficient outlier detection for data analysis within wireless sensor network (WSN) is a challenge. …”
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Efficient Cow Body Condition Scoring Using BCS-YOLO: A Lightweight, Knowledge Distillation-Based Method by Zhiqiang Zheng, Zhuangzhuang Wang, Zhi Weng

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Urban object detection algorithm based on feature enhancement and progressive dynamic aggregation strategy by Luxuan Bian, Zijun Gao, Jue Wang, Bo Li

“…Traditional target detection models face challenges in recognizing urban high-altitude remote sensing targets due to complex background noise and significant variations in target scale. …”
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NevusCheck: A Dysplastic Nevi Detection Model Using Convolutional Neural Networks by Andreluis Ingaroca-Torres, Lucía Heredia-Moscoso, Alvaro Aures-García

“…Therefore, the research aims to develop a model to diagnose dysplastic nevi using a deep learning network whose classification is based on the pre-trained architecture EfficientNet-B7, which was selected for its high classification accuracy and low computational complexity. …”
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A Novel YOLOv10-Based Algorithm for Accurate Steel Surface Defect Detection by Liefa Liao, Chao Song, Shouluan Wu, Jianglong Fu

“…The system uses only 2.67 million parameters, demonstrating efficiency. It excels in identifying complex defects like ’rolled in scale’ and ’inclusion’. …”
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Vehicle detection method based on multi-layer selective feature for UAV aerial images by Yinbao Ma, Yuyu Meng, Jiuyuan Huo

“…However, this task remains challenging due to variable high-altitude viewpoints, complex environmental interference, and limitations in algorithmic efficiency. …”
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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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GLLR-HAD: Global-local low-rank integration for hyperspectral image anomaly detection by Yu Bai, Yanling Zhang, Lili Zhang, Tan Zhao

“…Abstract Hyperspectral imaging (HSI), with its rich spectral and spatial information, offers unique advantages for anomaly detection. However, existing methods often struggle to simultaneously model global structures and local discriminative features, which hampers their ability to detect structural anomalies and adapt to spectral variability in complex scenarios. …”
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Mt or not Mt: Temporal variation in detection probability in spatial capture-recapture and occupancy models by Sollmann, Rahel

“…Here, I investigate whether closed spatial capture-recapture (SCR) and single season occupancy models are robust to ignoring temporal variation in detection probability. Ignoring temporal variation allows collapsing detection data across repeated sampling occasions, speeding up computations, which can be important when analyzing large datasets with complex models. …”
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Design and Validation of a Lightweight Entropy-Based Intrusion Detection Algorithm for Automotive CANs by Jiacheng Chen, Zhifu Wang

“…This work provides a resource-efficient security framework compatible with existing CAN infrastructures, effectively balancing attack detection efficacy with the operational constraints of automotive embedded systems.…”
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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

“…The experiments show that the sparse parallel attention mechanism offers significant advantages in disease detection with multi-scale and complex backgrounds. …”
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A Real-Time Lane Detection Algorithm Based on Intelligent CCD Parameters Regulation by Ping-shu Ge, Lie Guo, Guo-kai Xu, Rong-hui Zhang, Tao Zhang

“…Lane detection is one of the key techniques for LDWS. To overcome the contradiction between complexity of algorithm and the real-time requirement for vehicle onboard system, this paper introduces a new lane detection method based on intelligent CCD parameters regulation. …”
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Geometric Shaping for Distortion-Limited Intensity Modulation/Direct Detection Data Center Links by Ethan M. Liang, Joseph M. Kahn

“…Intra-data center links are subject to transmission impairments that pose challenges for efficient scaling of per-wavelength data rates beyond 100 Gb/s. …”
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