Towards lightweight model using non-local-based graph convolution neural network for SQL injection detection by Duc-Chinh Nguyen, Manh-Hung Ha, Manh-Tuan Do, Oscal Tzyh-Chiang Chen

“…To address this issue, we propose a unique graph network, an innovative topology not explored previously for SQL injection detection. SQL statements are nodes, and their connections form edges in the graph. …”
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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

“…Testing on small sample datasets further demonstrates MoSViT's generalization capability and potential for small-sample detection scenarios.…”
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Error Rate Analysis of Quantum-Annealing-Aided Multi-User Detection in Power-Domain Nonorthogonal Multiple Access by Kouki Yonaga, Kenichi Takizawa, Masaru Inaba

“…We present the error rate performance of quantum-annealing-aided multiuser detection (QA-aided MUD), a signal detection approach that combines quantum annealing (QA) with conventional iterative multiuser detection (MUD). …”
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A Relative Attitude Detection Method for Unmanned Aerial Vehicles Based on You Only Look Once Framework by Jingting Qiu, Feifan Yu, Fengrui Xu, Xinmin Chen, Jiqiang Wang

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A novel approach for breast cancer detection using a Nesterov accelerated adam optimizer with an attention mechanism by Abeer Saber, Tamer Emara, Samar Elbedwehy, Esraa Hassan

“…Abstract Image-based automatic breast tumor detection has become a significant research focus, driven by recent advancements in machine learning (ML) algorithms. …”
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Accurate Detection and Tracking of Small-Scale Vehicles in High-Altitude Unmanned Aerial Vehicle Bird-View Imagery by Heshan Zhang, Xin Tan, Mengwei Fan, Cunshu Pan, Zhanji Zheng, Shuang Luo, Jin Xu

“…Based on the original YOLOX network, a shallow feature extraction network, 160 × 160 pixels, is added to enhance the ability to extract small-scale object features. A convolutional block attention module (CBAM) is inserted in front of the neck network to select crucial information for vehicle detection tasks while suppressing noncritical ones. …”
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Detection of Crack Sealant in the Pretreatment Process of Hot In-Place Recycling of Asphalt Pavement via Deep Learning Method by Kai Zhao, Tianzhen Liu, Xu Xia, Yongli Zhao

“…Furthermore, the DRBNCSPELAN (Dilated Reparam Block with Cross-Stage Partial and Efficient Layer Aggregation Networks) module is introduced to ensure efficient information flow, and a lightweight shared convolution (LSC) detection head is developed. …”
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RHS-YOLOv8: A Lightweight Underwater Small Object Detection Algorithm Based on Improved YOLOv8 by Yifan Wei, Jun Tao, Wenjun Wu, Donghua Yuan, Shunzhi Hou

“…Finally, a small object detection branch is incorporated into the original architecture to enhance the model’s performance in detecting small objects. …”
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Dilated Convolution and YOLOv8 Feature Extraction Network: An Improved Method for MRI-Based Brain Tumor Detection by Lincy Annet Abraham, Gopinath Palanisamy, Veerapu Goutham

“…Hence this paper, Dilated Convolution and YOLOv8 Feature Extraction Network (DC-YOLOv8FEN) is proposed to improve tumor detection accuracy. To begin, the feature extraction network (FEN) is improved with the help of the self shuffle attention (SSA), and the feature map is maximized with the help of vision transformer block. …”
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Parameter-Efficient Fine-Tuning for Individual Tree Crown Detection and Species Classification Using UAV-Acquired Imagery by Jiuyu Zhang, Fan Lei, Xijian Fan

“…The experimental results demonstrate that the proposed ASCS fine-tuning method, which utilizes a small number of task-specific learnable parameters, significantly outperforms the latest YOLO detection framework and surpasses the state-of-the-art PEFT method in tree detection and classification tasks. …”
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YOLO-RDM: A high accuracy and efficient algorithm for magnetic tile surface defect detection with practical applications. by Wei Niu, Cheng Lv, Enxu Zhang, Zhongbin Wei

“…Traditional magnetic tile defect detection mainly relies on manual inspection and faces challenges like low detection accuracy and high cost. …”
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Very-Large-Scale Integration-Friendly Method for Vital Activity Detection with Frequency-Modulated Continuous Wave Radars by Krzysztof Ślot, Piotr Łuczak, Paweł Kapusta, Sławomir Hausman, Arto Rantala, Jacek Flak

“…A simple algorithm for respiratory activity detection in data produced by Frequency-Modulated Continuous-Wave (FMCW) radars is presented in this paper. …”
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LightYOLO: Lightweight model based on YOLOv8n for defect detection of ultrasonically welded wire terminations by Jianshu Xu, Lun Zhao, Yu Ren, Zhigang Li, Zeshan Abbas, Lan Zhang, Md Shafiqul Islam

“…Defect inspection of the surface in ultrasonically welded wire terminations is an important inspection procedure to ensure welding quality. However, the detection task of ultrasonic welding defects based on deep learning still faces the challenges of low detection accuracy and slow inference speed. …”
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Signal Detection in Intelligent Reflecting Surface-Assisted NOMA Network Using LSTM Model: A ML Approach by Haleema Sadia, Hafsa Iqbal, Syed Fawad Hussain, Nasir Saeed

“…Further, to optimize the phase shifts of IRS, we exploit a low complexity iterative solution using the element-wise block coordinate descent (EBCD) method. Monte Carlo simulations are performed to analyze the performance of the proposed scheme, and the findings show a considerable improvement in channel estimation and signal detection using the LSTM based IRS-NOMA receiver. …”
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Spike-Driven Channel-Temporal Attention Network with Multi-Scale Convolution for Energy-Efficient Bearing Fault Detection by JinGyo Lim, Seong-Eun Kim

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LGC-YOLO: Local-Global Feature Extraction and Coordination Network With Contextual Interaction for Remote Sensing Object Detection by Qinggang Wu, Yang Li, Junru Yin, Xiaotian You

“…First, LGSFE captures local and global features of dense objects through receptive-field attention convolution and global pooling in a multibranch structure, which effectively alleviates the misalignment between the extracted features of objects and their intrinsic characteristics, thereby providing more accurate and abundant features for subsequent object detection. Second, GOSII is designed to dynamically adjust the weights of each feature channel through combining SRU blocks and the SimAM attention mechanism, which are further optimized and embedded into C2f to enhance the representation ability of contextual features. …”
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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

“…Target detection in UAV images is of great significance in fields such as traffic safety, emergency rescue, and environmental monitoring. …”
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A Lightweight Semantic- and Graph-Guided Network for Advanced Optical Remote Sensing Image Salient Object Detection by Jie Liu, Jinpeng He, Huaixin Chen, Ruoyu Yang, Ying Huang

“…In recent years, numerous advanced lightweight models have been proposed for salient object detection (SOD) in optical remote sensing images (ORSI). …”
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MED-AGNeT: An attention-guided network of customized augmentation of samples based on conditional diffusion for textile defect detection by Jun Liu, Haolin Li, Hao Liu, Jiuzhen Liang

“…Its feature extraction module employs a dual-branch information residual unit (DIRU) as a substitute for the conventional convolution block, which combines the feature extraction capabilities of global pooling and max pooling, reducing the number of parameters while also achieving a certain improvement in detection results. …”
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YO-AFD: an improved YOLOv8-based deep learning approach for rapid and accurate apple flower detection by Dandan Wang, Dandan Wang, Huaibo Song, Huaibo Song, Huaibo Song, Bo Wang

“…The timely and accurate detection of apple flowers is crucial for assessing the growth status of fruit trees, predicting peak blooming dates, and early estimating apple yields. …”
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