Applications of aeromagnetic data to detect the Basement Tectonics of Eastern Yemen region by Ahmed S. Abu El-Ata, Ahmed A. EI-Khafeef, Ashraf E. Ghoneimi, Sami H. Abd Alnabi, Marwan A. Al-Badani

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Crack Detection Method of Sleeper Based on Cascade Convolutional Neural Network by Liming Li, Shubin Zheng, Chenxi Wang, Shuguang Zhao, Xiaodong Chai, Lele Peng, Qianqian Tong, Ji Wang

“…Results show that this method can accurately detect the sleeper crack image. During object detection, the proposed method is compared with YOLOv3 in terms of directly locating sleeper cracks. …”
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Photoacoustic Flow Cytometry for Single Sickle Cell Detection In Vitro and In Vivo by Chengzhong Cai, Dmitry A. Nedosekin, Yulian A. Menyaev, Mustafa Sarimollaoglu, Mikhail A. Proskurnin, Vladimir P. Zharov

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Automated Sidewalk Surface Detection Using Wearable Accelerometry and Deep Learning by Do-Eun Park, Jong-Hoon Youn, Teuk-Seob Song

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HEAT: Incorporating hierarchical enhanced attention transformation into urban road detection by Ting Han, Chuanmu Li, Siyu Chen, Zongyue Wang, Jinhe Su, Yundong Wu, Guorong Cai

“…Abstract Road detection plays a vital role in automated driving and advanced driver assistance systems. …”
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THREE-DIMENSIONAL DETECTION OF GAMMA RADIATION AND POLLUTING GASES USING QUADROCOPTERS by A. Molnar

“…Accurate knowledge of the extent and local distribution of pollution plays a key role in many areas of life.Method. …”
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Detection of breast cancer using machine learning and explainable artificial intelligence by Tharunya Arravalli, Krishnaraj Chadaga, H Muralikrishna, Niranjana Sampathila, D. Cenitta, Rajagopala Chadaga, K. S. Swathi

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Pedestrian dynamics modeling and social force analysis based on object detection by Fangyan Yang, Rong Liu, Daoyu Zhu

“…IntroductionObject detection is a fundamental component of modern computational applications, playing a crucial role in pedestrian analysis, autonomous navigation, and crowd monitoring. …”
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A lightweight MHDI-DETR model for detecting grape leaf diseases by Zilong Fu, Lifeng Yin, Can Cui, Yi Wang

“…This structure is designed to overcome the challenges of capturing complex high-level and subtle low-level features, and it uses Efficient Local Attention to focus more efficiently on regions of interest, thereby enhancing the model’s ability to detect complex targets while improving accuracy and inference speed. …”
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Developing an Early Detection Model for improving Vector-Borne Disease Surveillance by A. Raisinghani, K. Saha

“…However, most of the study have been limited to district level and few climatic variables, which may not be sufficient for localized mitigation efforts. To bridge this gap an Early Detection model for dengue fever is developed, analysing key spatial-temporal variables influencing local transmission. …”
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Attention-based BiLSTM with positional embeddings for fake review detection by Jindong Chen, Tian Zhang, Zhihua Yan, Zhichao Zheng, Wen Zhang, Jian Zhang

“…Then, the sequence model BiLSTM is employed to extract sequential features from the text, while HAM is applied to effectively weight both global and local features, ensuring the accurate capture and transmission of key information. …”
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SD-YOLOv8: Automated Motion Detection System for Aerobics Students by Lian Tang, Ya Li, Qing Du, Jincheng Liang

“…Then, based on the YOLOv8 network architecture, we implemented two key improvements: 1) introducing Selective Kernel Networks (SKNet) in the multi-scale feature fusion layer to enhance local feature capture capabilities; 2) replacing the original detection head with Dynamic Head to effectively reduce the computational burden while improving detection accuracy and efficiency. …”
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Remote Sensing Small Object Detection Based on Multicontextual Information Aggregation by Jingyu Wang, Mingrui Ma, Pengfei Huang, Shaohui Mei, Liang Zhang, Hongmei Wang

“…Due to wide field of view and background confusion, remote sensing objects are small and densely packed, hence commonly used detection methods detecting small objects are not satisfactory. …”
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Detection of Potential Bacterial Pathogens and Aflatoxigenic Fungi from Grain Samples by Hinda Abdukadir Mohamed, Md. Salauddin, Md. Khaled Hossain, Farzana Afroz

“…Current research work was carried out for the detection of potential bacterial pathogen and aflatoxigenic fungi Aspergillus spp. from grain comprising [Rice (5), Maize (5), Wheat (5), Khessari dal (5) and Anchora dal (5)] were collected from 3 different local markets of Dinajpur District, Bangladesh. 15 bacterial isolates comprising 4 genera of bacteria were found from a total of 25 samples. …”
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The Application of Kalman Filter Algorithm in Rail Transit Signal Safety Detection by Zhinong Miao, Qilong Liao

“…The rail communication transmission system is also affected by interference from wireless local area networks and rail foreign objects, leading to signal transmission failures. …”
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SMS spam detection using BERT and multi-graph convolutional networks by Linjie Shen, Yanbin Wang, Zhao Li, Wenrui Ma

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A Comprehensive Method for Anomaly Detection in Complex Dynamic IoT Systems by Andrii Liashenko, Larysa Globa

“…In this paper, we propose a novel anomaly detection approach that combines Temporal Graph Neural Networks (TGNN) with Autoencoders. …”
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Using 'sentinel' plants to improve early detection of invasive plant pathogens. by Francesca A Lovell-Read, Stephen Parnell, Nik J Cunniffe, Robin N Thompson

“…Our results demonstrate that including sentinel plants in monitoring programmes can reduce the expected prevalence of infection upon outbreak detection substantially, increasing the feasibility of local outbreak containment.…”
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Barefoot Footprint Detection Algorithm Based on YOLOv8-StarNet by Yujie Shen, Xuemei Jiang, Yabin Zhao, Wenxin Xie

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Utilize Data Augmentation and Flexi Corner Block for Road Damage Detection by Zhaohui Wu, Runjing Zhao, Xingliang Sun, Zhaojia Li

“…The Weather Trim Augment module leverages stable diffusion to generate weather-specific road damage datasets by adjusting prompt words and parameters, ensuring crack location and type remain unchanged, thus improving detection under various weather conditions. The Flexi Corner Block module enhances road damage detection by combining deformable convolutions with lightweight MLP and Learnable Local Attention, improving feature learning in corner areas. …”
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