Reliable and efficient magnetic data inversion for resource detection using a hybrid bat algorithm by Khalid S. Essa, Mahmoud Elhussein, Omar A. Gomaa, Zein E. Diab

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Experimental Research on and Optimization of Plasma Emitter Sources by Xu Gao, Jing Zhou, Xiao Du

“…The emitter has significant application potential in areas such as onshore and offshore oil and gas exploration, unconventional resource detection, impulse wave fracturing and wellbore clearance, and rescue and U-well drilling.…”
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MSA: Mamba Semantic Alignment Networks for Remote Sensing Change Detection by Zhenyang Huang, Peng Duan, Genji Yuan, Jinjiang Li

“…It is widely used in areas, such as urban expansion, disaster assessment, and resource detection. Current deep learning-based CD methods typically extract feature information from remote sensing images through downsampling and then aggregate early features with deeper ones during upsampling. …”
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Sequential Inversion for Helicopter Time-Domain Electromagnetics Based on a Regularized Extended Kalman Filtering by Sirui Zhou, Jun Lin, Chuandong Jiang, Haigen Zhou, Yanzhang Wang

“…The helicopter time-domain electromagnetic method (HTEM) has been widely applied in challenging geological terrains, particularly in large-scale mineral exploration, underground water resource detection, and the selection of sites for underground engineering, due to its advantage of not requiring personnel to enter the detection area. …”
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Novel and Optimized Efficient Transmission Using Dynamic Routing Technique for Underwater Acoustic Sensor Networks by Swapna Babu, Bhuvaneswari Subramanian, Sujitha Madhavadhas, Kavitha Ganesan, Manjula Dhandapani, Surendiran Muthukumar Deva

“…Underwater acoustic sensor networks involve deploying sensors underwater in order to establish a wireless network framework aimed at discovering new resources, detecting targets, and monitoring pollution. However, the primary challenge in these networks lies in enhancing energy efficiency and extending the sensor’s lifespan, as manually recharging batteries deep within the sea or ocean is not feasible. …”
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A novel approach combining YOLO and DeepSORT for detecting and counting live fish in natural environments through video. by Nguyen Minh Khiem, Tran Van Thanh, Nguyen Hung Dung, Yuki Takahashi

“…Applying Artificial Intelligence (AI) to the monitoring of live fish in natural environments represents a promising approach to the sustainable management of aquatic resources. Detecting and counting fish in water through video analysis is crucial for fish population statistics. …”
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Automatic detection and extraction of key resources from tables in biomedical papers by Ibrahim Burak Ozyurt, Anita Bandrowski

“…Conclusions Our pipelines allow the detection and extraction of key resources from tables with much higher accuracy, enabling the deployment of automated research resource extraction tools on BioRxiv to help authors correct unidentifiable key resources detected in their articles and improve the reproducibility of their findings. …”
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