Sowing, Monitoring, Detecting: A Possible Solution to Improve the Visibility of Cropmarks in Cultivated Fields by Filippo Materazzi

“…This interdisciplinary approach also engaged local stakeholders, including students from the Istituto Agrario Midossi, fostering educational opportunities and community involvement. …”
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3D data augmentation and dual-branch model for robust face forgery detection by Changshuang Zhou, Frederick W.B. Li, Chao Song, Dong Zheng, Bailin Yang

“…We propose Dual-Branch Network (DBNet), a novel deepfake detection framework that addresses key limitations of existing works by jointly modeling 3D-temporal and fine-grained texture representations. …”
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Detection of terrain feature points from digital elevation models using contour context by Jiapei Hu, Xuejun Liu, Bo Wu

“…This proposed approach not only avoids the spurious feature points produced by the local window method, but also prevents the omission of valid points and the creation of redundant ones. …”
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Detection Algorithm for Key Components on High-speed Railways: Reconstruction Based on Spike Data by DONG Wenbo, LI Chen, XIONG Minjun, TIAN Ye, XIAO Xiong, YAO Weiwei

“…The accurate and fast localization of key components on high-speed railways in operation serves is one of the foundations for fault diagnosis of high-speed railways. …”
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CNN-ViT: A multi-feature learning based approach for driver drowsiness detection by Madduri Venkateswarlu, Venkata Rami Reddy Chirra

“…This hybrid framework is designed to harness the complementary strengths of CNNs and transformers: CNNs excel at capturing fine-grained local features, while ViT effectively models global dependencies within images. …”
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Improvement of Organizational Measures for Detection and Diagnosing of Tuberculous Infection and Tuberculosis in Adolescents in the Republic of Kazakhstan by L. T. Eralieva, K. S. Serikbaeva, A. S. Rakisheva, Z. S. Bekbenbetova, O. G. Prikhodchenko

“…The objective: to improve organizational measures for detection and diagnosing of tuberculous infection and tuberculosis in adolescents in the Republic of Kazakhstan.Subjects and Methods. …”
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Revisiting Wolbachia detections: Old and new issues in Aedes aegypti mosquitoes and other insects by Perran A. Ross, Ary A. Hoffmann

“…However, since our review, more and more papers are emerging on Wolbachia detections in this species. Our purpose here is to evaluate these papers within the context of criteria we previously established but also new criteria that include the absence of releases of transinfections within the local areas being sampled which has contaminated natural populations in at least one case where novel detections have been reported. …”
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Multi-Scale Twin Networks for Coastal Zone Change Detection in Remote Sensing Imagery by Peiqi Zhu, Xiaoyi Jiang, Qi He, Longfei Zhao, Yu Hong, Xue Guo, Hanrui Sun

“…These modules allow the model to focus on both global and local changes, enhancing its ability to detect variations in coastal zones. …”
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Fault detection for Li-ion batteries of electric vehicles with feature-augmented attentional autoencoder by Yunsheng Fan, Zhiwu Huang, Heng Li, Wei Yuan, Lisen Yan, Yongjie Liu, Zheng Chen

“…Then, the augmented features are input into the local outlier factor algorithm for battery fault detection. …”
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Detecting Positive and Negative Changes From SAR Images by an Evolutionary Multi-Objective Approach by Shuang Liang, Hao Li, Yun Zhu, Maoguo Gong

“…This paper presents an unsupervised change detection approach for detecting the positive and negative changes based on a multi-objective evolutionary algorithm. …”
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MOLECULAR DETECTION OF TETRACYCLINE RESISTANCE GENES IN Bacillus cereus ISOLATED FROM FOOD SOURCES by Ban M.S. Saeed, Basil A. Abbas, Shaker A.N. Al-jadaan

“…Polymerase chain reaction was used for detection of the presence oftetracycline resistance gene in the percentage 32 % and 44% for tet (K) and tet (L), respectively.…”
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Explainable AI supported hybrid deep learnig method for layer 2 intrusion detection by Ilhan Firat Kilincer

“…This study proposes the creation of a Comprehensive Layer 2 − IDS (CL2-IDS) dataset for the development of IDS systems utilised in the local network structures of organisations, in conjunction with a hybrid deep learning (DL) model for the detection of attack vectors in the proposed dataset. …”
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Deep learning-based occlusion-aware face mask detection for airborne disease control by Teshome Ayechiluhem Yalew, Sosina M. Gashaw, Aleka Melese Ayalew, Mourad Oussalah

“…In this study, we collect data from public and local sources to develop an occlusion-aware face mask detection model. …”
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Federated Learning-Assisted Coati Deep Learning-Based Model for Intrusion Detection in MANET by S. Faizal Mukthar Hussain, S. M. H. Sithi Shameem Fathima

“…Federated learning with GAN networks allows for the aggregation of updates from multiple local models distributed across MANET. Assessment metrics such as accuracy, precision, F1 score, detection rate, recall, and security rate have been utilized to assess the efficacy of the proposed HIDE-MAN method. …”
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Interpretable adaptive fault detection method for smart grid based on belief rule base by Yingmei Li, Yaopu Bai, Ruohan Yang, Zhichao Feng, Wei He

“…In addition, in order to avoid falling into the local optimal solution in the optimization process, the search domain is updated adaptively according to the accuracy of the model, which improves the interpretability and robustness of the fault detection model. …”
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Axial-UNet++ Power Line Detection Network Based on Gated Axial Attention Mechanism by Ding Hu, Zihao Zheng, Yafei Liu, Chengkang Liu, Xiaoguo Zhang

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SCASNet: Spatial Context-Aware Selection Network for Small Object Detection in Aerial Imagery by Zhenkuan Wang, Xue-Mei Dong, Yongli Xu

“…The detection of small objects within intricate backgrounds poses a significant challenge in the domain of aerial image object detection. …”
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Point-Level Fusion and Channel Attention for 3D Object Detection in Autonomous Driving by Juntao Shen, Zheng Fang, Jin Huang

“…PointPillars transforms point cloud data into a two-dimensional pseudo-image and employs a 2D CNN for efficient and precise detection. Nevertheless, this approach encounters two primary challenges: (1) the sparsity and disorganization of raw point clouds hinder the model’s capacity to capture local features, thus impacting detection accuracy; and (2) existing models struggle to detect small objects within complex environments, particularly regarding orientation estimation. …”
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DScanNet: Packaging Defect Detection Algorithm Based on Selective State Space Models by Yirong Luo, Yanping Du, Zhaohua Wang, Jingtian Mo, Wenxuan Yu, Shuihai Dou

“…To address the problem that the model’s detailed feature extraction for small target defects is not sufficient and thus leads to low detection accuracy, the MEFE module, the local feature extraction module (LFEM Block), and the PCR module of the multi-scale convolution and feature enhancement strategy are proposed to enhance the model’s capability of capturing defective features and focusing on specific features, and to improve the detection accuracy. …”
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Anomaly Detection in Network Traffic via Cross-Domain Federated Graph Representation Learning by Yanli Zhao, Zongduo Liu, Junjie Pang

“…To further improve the model’s generalization across domains, a cross-domain structural guidance mechanism is implemented on the server side, which integrates structural information from multiple domains to guide the training of local models. Comparative experiments with other methods demonstrate that the proposed approach achieves superior performance in distributed network traffic anomaly detection scenarios.…”
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