Research and Application of a Multitarget Detection Algorithm Based on Improved YOLOv8 for Indoor Objects by Yanzhen Wang, Wei Wang, Xiaolong Zhou, Xubin Dong, Jianyong Li, Qi Zhao, Xinyu Yang, Yao Wang

“…First, the GAM global attention mechanism is embedded in the backbone network of YOLOv8 to improve the sensitivity of the backbone network to the important feature information and reduce the attention to the irrelevant features, and it is determined that the GAM global attention mechanism will be embedded in the backbone network of YOLOv8 after comparing and analyzing the GAM with the attention mechanisms of CBAM, SE, and ECA; second, at the neck layer, the original PAN-FPN network structure is replaced with the BiFPN structure at the neck layer to realize bidirectional cross-scale connectivity and weighted feature fusion. …”
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Synthesis of a reversible quantum Vedic multiplier on IBM quantum computers by Mojtaba Noorallahzadeh, Mohammad Mosleh

“…This Toffoli-based network is then optimized using various techniques, ultimately transforming it into a network of fundamental quantum gates. …”
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BED-YOLO: An Enhanced YOLOv10n-Based Tomato Leaf Disease Detection Algorithm by Qing Wang, Ning Yan, Yasen Qin, Xuedong Zhang, Xu Li

“…Second, we incorporated a Bidirectional Feature Pyramid Network (BiFPN) on top of the FPN + PAN structure to optimize feature fusion and improve the extraction of small disease regions, thereby enhancing the detection accuracy for small lesion targets. …”
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An efficient fire detection algorithm based on Mamba space state linear attention by Yuming Li, Yongjie Wang, Xiaorui Shao, Anbo Zheng

“…Instead, it performs dimensionality reduction on input features through adaptive average pooling and utilizes the state update mechanism of the SSM module to significantly enhance feature representation and optimize information flow. …”
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An Auction-Based Bid Prediction Mechanism for Fog-Cloud Offloading Using Q-Learning by Reza Besharati, Mohammad Hossein Rezvani, Mohammad Mehdi Gilanian Sadeghi

“…The evaluation results show that the bid values predicted by the Q-learning method are near-optimal. On average, the proposed method consumes less energy than traditional and state-of-the-art techniques. …”
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An Interpretable Siamese Attention Res-CNN for Fingerprint Spoofing Detection by Chengsheng Yuan, Zhenyu Xu, Xinting Li, Zhili Zhou, Junhao Huang, Ping Guo

“…Furthermore, to highlight the difference in RCF, a Siamese attention residual network is devised, and the ridge continuity amplification loss function is designed to optimize the training process. …”
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Combining Transfer Learning and Ensemble Algorithms for Improved Citrus Leaf Disease Classification by Hongyan Zhu, Dani Wang, Yuzhen Wei, Xuran Zhang, Lin Li

“…We proposed the Multi-Models Fusion Network (MMFN) for citrus leaf diseases detection based on model fusion and transfer learning. …”
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Classification-based point cloud denoising and 3D reconstruction of roadways by Denghong CHEN, Ning PANG, Wen NIE, Juqiang FENG, Jiliang KAN, Jinjing ZHANG

“…This algorithm delivered adaptive optimization performance, yielding types Ⅰ and Ⅱ errors of 1.54 % and 5.37 %, respectively. …”
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International trade market forecasting and decision-making system: multimodal data fusion under meta-learning by Yiming Bai, Muhammad Asif

“…In the feature fusion stage, a meta-learning bidirectional feature pyramid network (ML-BiFPN) is proposed to refine the interaction of multi-scale information via a bidirectional feature pyramid structure. …”
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Federated Knowledge Distillation With 3D Transformer Adaptation for Weakly Labeled Multi-Organ Medical Image Segmentation by Tareq Mahmod AlZubi, Hamza Mukhtar

“…To address these challenges, we propose the Federated 3D Knowledge Distillation Network (Fed3D-KDNet), a hybrid federated learning (FL) framework that integrates both global and local knowledge distillation mechanisms. …”
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Carbon footprint of private dental laboratories in Egypt: A cross-sectional study by Amira H. Elwan, Ahmed Mahmoud Fouda

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Real-Time Heterogeneous Collaborative Perception in Edge-Enabled Vehicular Environments by Samuel Thornton, Nithin Santhanam, Rajeev Chhajer, Sujit Dey

“…The proposed CaLPeN model outperforms six implemented comparison models in terms of effective mean average precision (EmAP), beating the next best model's performance by 5.5% on average when tested on the OPV2V perception dataset using two different combinations of wireless communication conditions and vehicular sensor/computing distributions.…”
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Robust Classification of UWB NLOS/LOS Using Combined FCE and XGBoost Algorithms by Shoude Wang, Nur Syazreen Ahmad

“…Compared to traditional machine learning and neural networks, it offers lower system requirements. Experimental results on an open-source dataset covering seven scenarios show average accuracy, precision, recall, and F1 score of 93.2%, 94.8%, 90.3%, and 92.5%, respectively, highlighting the method’s superior performance and robustness in diverse environments.…”
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Improvement of English-Chinese bilingual learning by integrating semantic analysis and neural machine translation by Yue Zhao, Qilin Wang

“…Abstract To improve the effectiveness of English-Chinese bilingual learning, this study introduces an optimization model that combines semantic analysis with neural machine translation (NMT). …”
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Advancing road maintenance with EfficientDet-based pothole monitoring by Jenefa Archpaul, Taurshia Antony, Kuriakose Bessy Mani, Kumar Edward Naveen Vijaya, Lincy Archpaul

“…Moreover, we provide a comparative analysis with five contemporary pothole detection algorithms: YOLOv5, RetinaNet, CenterNet, SSD, and Faster R-CNN, among which EfficientDet consistently shows superior performance in terms of precision, recall, F1-Score, and average precision. These findings highlight the significant advancements in road safety, infrastructure management, and resource optimization. …”
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An Energy-Domain IR NUC Method Based on Unsupervised Learning by Ting Li, Xuefeng Lai, Sheng Liao, Yucheng Xia

“…The results show that the trained correction network is uniform and produces stable outputs when the integration time and attenuator change within the optimal dynamic range. …”
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YOLO-SG: Seafloor Topography Unit Recognition and Segmentation Algorithm Based on Lightweight Upsampling Operator and Attention Mechanisms by Yifan Jiang, Ziyin Wu, Fanlin Yang, Dineng Zhao, Xiaoming Qin, Mingwei Wang, Qiang Wang

“…The SG-MKD dataset provides instance segmentation annotations for three types of seafloor topographic units—seamounts, sea knolls, and submarine depressions—across a total of 419 images. YOLO-SG is an optimized version of the YOLOv8l-Segment model, incorporating a convolutional block attention module in the backbone network to enhance feature extraction. …”
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Investigation on the Aerodynamic Parameters of the Triangle Shape of Tall Buildings by Using of CFD Method by Mehdi Noormohamadian, Eysa Salajegheh

“…Nowadays, the neural network algorithm is one of the most famous numerical methods for optimizing hull shapes. …”
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Surface Classification from Robot Internal Measurement Unit Time-Series Data Using Cascaded and Parallel Deep Learning Fusion Models by Ghaith Al-refai, Dina Karasneh, Hisham Elmoaqet, Mutaz Ryalat, Natheer Almtireen

“…The models were trained on a normalized Internal Measurement Unit (IMU) dataset, with hyperparameter tuning achieved via grid search for optimal performance. Results showed that the cascaded model achieved higher accuracy metrics, including a mean Average Precision (mAP) of 0.721 compared to 0.693 for the parallel model. …”
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A Lightweight Algorithm for Detection and Grading of Olive Ripeness Based on Improved YOLOv11n by Fengwu Zhu, Suyu Wang, Min Liu, Weijie Wang, Weizhi Feng

“…The proposed approach employs YOLOv11n as the baseline model, replaces its backbone network with EfficientNet-B0, and integrates the Large-Scale Kernel Attention (LSKA) mechanism and the Bidirectional Feature Pyramid Network (BiFPN). …”
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