Application of VGG16 in Automated Detection of Bone Fractures in X-Ray Images by Resky Adhyaksa, Bedy Purnama

“…The training and testing phases utilized an 80:20 split of the data, employing binary cross-entropy as the loss function and the Adam optimizer for efficient weight updates. …”
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Multi-Scale Construction Site Fire Detection Algorithm with Integrated Attention Mechanism by Haipeng Sun, Tao Yao

“…To address the issues of large target-scale variations and frequent false detections in construction site fire monitoring, we propose a fire detection algorithm based on an improved YOLOv8 model, achieving real-time and efficient detection of fires on construction sites. …”
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An Improved YOLOv7-Tiny-Based Algorithm for Wafer Surface Defect Detection by Mengyun Li, Xueying Wang, Hongtao Zhang, Xiaofeng Hu

“…Next, a lightweight convolutional module, ghost shuffle convolution (GSConv), is introduced into the feature fusion network to reduce the network’s parameter count while maintaining a certain level of detection accuracy. …”
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RP-DETR: end-to-end rice pests detection using a transformer by Jinsheng Wang, Tao Wang, Qin Xu, Lu Gao, Guosong Gu, Liangquan Jia, Chong Yao

“…Additionally, the MPDIoU-based loss function enhances the model’s detection performance. …”
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Protein composition and functional parameters of RBC membranes in liver and kidney transplantation by A. V. Deryugina, O. P. Abaeva, S. V. Romanov, M. V. Vedunova, E. N. Ryabova, S. A. Vasenin, N. A. Titova

“…The revealed changes in protein levels in the protein phase of RBC membranes were combined with functional indices of RBCs. In kidney recipients, decreased RBC electrophoretic mobility and increased aggregation were detected at 2 months. …”
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Detection of host-derived sphingosine by Pseudomonas aeruginosa is important for survival in the murine lung. by Annette E LaBauve, Matthew J Wargo

“…Deletion of sphR resulted in reduced bacterial survival during mouse lung infection. …”
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Applicability of Artificial Intelligence in Smart Healthcare Systems for Automatic Detection of Parkinson’s Disease by Harikumar Pallathadka, S.J.R.K. Padminivalli V., M. Vasavi, P. Nancy, Mohd Naved, Harish Kumar, Samrat Ray

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FSDN-DETR: Enhancing Fuzzy Systems Adapter with DeNoising Anchor Boxes for Transfer Learning in Small Object Detection by Zhijie Li, Jiahui Zhang, Yingjie Zhang, Dawei Yan, Xing Zhang, Marcin Woźniak, Wei Dong

“…This approach achieves a balance between computational efficiency for medium-resolution images and the accuracy required for small object detection. Our architecture also employs adapter modules to reduce re-training costs, and a two-stage fine-tuning strategy adapts fuzzy modules to specific domains before harmonizing the model with task-specific adjustments. …”
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Grape Target Detection Method in Orchard Environment Based on Improved YOLOv7 by Fuchun Sun, Qiurong Lv, Yuechao Bian, Renwei He, Dong Lv, Leina Gao, Haorong Wu, Xiaoxiao Li

“…In response to the poor detection performance of grapes in orchards caused by issues such as leaf occlusion and fruit overlap, this study proposes an improved grape detection method named YOLOv7-MCSF based on the You Only Look Once v7 (YOLOv7) framework. …”
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Rolling window for detecting multiple Chan signatures to diagnose excessive water production by Ahmed MohamedSalih Musa Hamdoon, A. P. Mohammed Abdalla Ayoub Mohammed, A. P. Khaled Abdalla Elraies

“…While machine learning models were developed to automate Chan plot interpretation and reduce human bias, they often failed to capture the evolution of water production over time, typically detecting only a single pattern or capturing patterns after it fully materialized, reducing the chance of early diagnosing. …”
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Fish Disease Detection Using Image Based Machine Learning Technique in Aquaculture by Md Shoaib Ahmed, Tanjim Taharat Aurpa, Md. Abul Kalam Azad

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Optimizing Car Collision Detection Using Large Dashcam-Based Datasets: A Comparative Study of Pre-Trained Models and Hyperparameter Configurations by Muhammad Shahid, Martin Gregurić, Amirhossein Hassani, Marko Ševrović

“…We evaluated several state-of-the-art (SOTA) image classification models and fine-tuned them using different hyperparameter combinations to test their performance on the car collision detection problem. Our methodology systematically investigates the influence of optimizers, loss functions, schedulers, and learning rates on model generalization. …”
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HTC-HAD: A Hybrid Transformer-CNN Approach for Hyperspectral Anomaly Detection by Minghua Zhao, Wen Zheng, Jing Hu

“…In addition, to prevent anomalies from being reconstructed during background estimation, we employ an adaptive weight loss function to suppress them. Experimental results on several real datasets, both qualitatively and quantitatively, demonstrate that our HTC-HAD achieves satisfying detection performance.…”
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Developing a Machine Vision System to Detect Weeds from Potato Plant by Yousef Abbaspour Gılandeh, Hossein Javadıkıa, Sajad Sabzı

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A Detection Method for Conveyor Belt Damage with Small Size and Low Contrast by HAN Yajie, HAO Xiaoli, NIU Baoning, XUE Jindong

“…By connecting features of different levels across layers, complete and rich multi-scale features can be obtained, and small-size damage detection can be completed. Second, the gradient harmonized mechanism is introduced into the classification loss function, and the weight of small-size damage is dynamically adjusted to make it fully trained. …”
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FedNDA: Enhancing Federated Learning with Noisy Client Detection and Robust Aggregation by Tuan Dung Kieu, Charles Fonbonne, Trung-Kien Tran, Thi-Lan Le, Hai Vu, Huu-Thanh Nguyen, Thanh-Hai Tran

“…The noisiness score is subsequently transfered to and used in the server-side aggregation function to prioritize clean clients while reducing the influence of noisy clients. …”
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Rice disease detection method based on multi-scale dynamic feature fusion by Qian Fan, Runhao Chen, Bin Li

“…In order to enhance the accuracy of rice leaf disease detection in complex farmland environments, and facilitate the deployment of the deep learning model onto mobile terminals for rapid real-time inference, this paper introduces a disease detection network titled YOLOv11 Multi-scale Dynamic Feature Fusion for Rice Disease Detection (YOLOv11-MSDFF-RiceD). …”
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A Rapid Concrete Crack Detection Method Based on Improved YOLOv8 by Yongzhen Wang, Jiacong He

“…Furthermore, the introduction of the GF_Detect detection head significantly reduces the number of model parameters while improving detection performance. …”
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EfficientTransformer: A Dynamic Anomaly Detection Model for Industrial Control Networks by Jinyang Liu, Guogang Wang, Xuejun Zong, Bowei Ning, Kan He

“…Additionally, to address the issue of class imbalance, the model incorporates a weighted cross-entropy loss function that assigns higher weights to the minority class of abnormal traffic, thereby improving the model’s anomaly detection ability. …”
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SVHAE: Spectral Variability-Aware Hybrid Autoencoder for Hyperspectral Underwater Target Detection by Suresh Aala, Sravan Kumar Sikhakolli, Sunil Chinnadurai, Anuj Deshpande, Karthikeyan Elumalai, Md. Abdul Latif Sarker, Hala Mostafa

“…Our method effectively reduces the effect of spectral distortions and addresses variability using a combined loss function integrating Kullback-Leibler divergence, mean squared error, and spectral angle distance. …”
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