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Application of CycleGAN-based low-light image enhancement algorithm in foreign object detection on belt conveyors in underground mines
Published 2025-07-01“…However, in underground environments, low illumination and uneven brightness can significantly degrade image quality, thereby affecting the detection of foreign objects in coal flow and reducing the reliability of safety monitoring equipment. …”
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An AI deep learning algorithm for detecting pulmonary nodules on ultra-low-dose CT in an emergency setting: a reader study
Published 2024-11-01“…Abstract Background To retrospectively assess the added value of an artificial intelligence (AI) algorithm for detecting pulmonary nodules on ultra-low-dose computed tomography (ULDCT) performed at the emergency department (ED). …”
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A belief propagation algorithm based on track‐before‐detect for tracking low‐observable and manoeuvering targets using multiple sensors
Published 2024-12-01“…Abstract It is notoriously challenging work to track an unknown number of low‐observable manoeuvering targets. In this paper, a sequential Bayesian inference method based on the multiple‐model dynamic model and track‐before‐detect measurement (TBD) model is proposed for tracking low‐observable manoeuvering targets using multiple sensors. …”
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A low complexity pilot assignment algorithm based on user polar coordinates in CF-mMIMO systems
Published 2023-07-01“…Absrtact: In order to reduce the pilot contamination in the cell-free massive multi-input multi-output (MIMO) system, a low complexity pilot assignment algorithm based on user polar coordinates was proposed.Firstly, a Gaussian weighted density algorithm was proposed to determine a centroid as the polar coordinates center point in the system coverage area, then pre-assigned the pilot in order according to the angular coordinates, so that users who reused the same pilot had a greater probability of having a longer distance, and henced reduce the pilot contamination.A low complexity distance detection algorithm was then proposed to ensure that the user spacing between any two users multiplexing the same pilot was greater than the threshold.The simulation results show that the proposed pilot assignment algorithm effectively reduce pilot contamination, improve the uplink throughput of 95% users of the system, and achieve a good compromise between performance and complexity.…”
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Early Detection of Voltage Instability: A Transparent, Rule-Based Method for Cyber-Resilient Grids
Published 2025-01-01“…This paper proposes a rule-based algorithm for fast prediction of long-term voltage stability status immediately after a disturbance, eliminating the need for post-disturbance measurements. …”
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Image forgery detection algorithm based on U-shaped detection network
Published 2019-04-01“…Aiming at the defects of traditional image tampering detection algorithm relying on single image attribute,low applicability and current high time-complexity detection algorithm based on deep learning,an U-shaped detection network image forgery detection algorithm was proposed.Firstly,the multi-stage feature information in the image by using the continuous convolution layers and the max-pooling layers was extracted by U-shaped detection network,and then the obtained feature information to the resolution of the input image through the upsampling operation was restored.At the same time,in order to ensure higher detection accuracy while extracting high-level semantic information of the image,the output features of each stage in U-shaped detection network would be merged with the corresponding output features through the upsampling layer.Further the hidden feature information between tampered and un-tampered regions in the image upon the characteristics of the general network was explored by U-shaped detection network,which could be realized quickly by using its end-to-end network structure and extracting the attributes of strong correlation information among image contexts that could ensure high-precision detection results.Finally,the conditional random field was used to optimize the output of the U-shaped detection network to obtain a more exact detection results.The experimental results show that the proposed algorithm outperforms those traditional forgery detection algorithms based on single image attribute and the current deep learning-based detection algorithm,and has good robustness.…”
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Image forgery detection algorithm based on U-shaped detection network
Published 2019-04-01“…Aiming at the defects of traditional image tampering detection algorithm relying on single image attribute,low applicability and current high time-complexity detection algorithm based on deep learning,an U-shaped detection network image forgery detection algorithm was proposed.Firstly,the multi-stage feature information in the image by using the continuous convolution layers and the max-pooling layers was extracted by U-shaped detection network,and then the obtained feature information to the resolution of the input image through the upsampling operation was restored.At the same time,in order to ensure higher detection accuracy while extracting high-level semantic information of the image,the output features of each stage in U-shaped detection network would be merged with the corresponding output features through the upsampling layer.Further the hidden feature information between tampered and un-tampered regions in the image upon the characteristics of the general network was explored by U-shaped detection network,which could be realized quickly by using its end-to-end network structure and extracting the attributes of strong correlation information among image contexts that could ensure high-precision detection results.Finally,the conditional random field was used to optimize the output of the U-shaped detection network to obtain a more exact detection results.The experimental results show that the proposed algorithm outperforms those traditional forgery detection algorithms based on single image attribute and the current deep learning-based detection algorithm,and has good robustness.…”
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Graph-Theoretic Detection of Anomalies in Supply Chains: A PoR-Based Approach Using Laplacian Flow and Sheaf Theory
Published 2025-05-01“…Based on Graph Balancing Theory, this study proposes an anomaly detection algorithm, the Supply Chain Proof of Relation (PoR), applied to enterprise procurement networks formalized as weighted directed graphs. …”
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Efficient attack detection and data aggregation algorithm
Published 2012-09-01“…An efficient algorithm of attack detection and data aggregation for wireless multimedia sensor networks based on the previous work was proposed.The proposed algorithm concludes the action trait of sensor nodes from their attribute vectors without any prior knowledge,at the same time;it was scalable and could be applied in large scale net-works.The simulation results show that the proposed algorithm can detect the attacks action more accurate than other technologies,and can make data aggregation efficiently.At the same time,the proposed algorithm can make the wireless multimedia sensor networks secure and reduce communication flow so that it will save a lot of resources in wireless mul-timedia sensor networks.…”
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Shot boundary detection algorithm based on ORB
Published 2013-11-01“…The existing algorithms of SBD show low robustness when there exist camera or object movements, light changes in the scene. …”
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Low-Complexity Gaussian Detection for MIMO Systems
Published 2010-01-01“…Using factor graphs as a general framework and applying the Gaussian approximation, three low-complexity iterative detection algorithms are derived, and their performances are compared by means of Monte Carlo simulations. …”
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Evaluation of Automated Object-Detection Algorithms for Koala Detection in Infrared Aerial Imagery
Published 2024-10-01“…The implementation of infrared cameras and drones has demonstrated encouraging outcomes, regardless of whether the detection was performed by human observers or automated algorithms. …”
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An efficient interpretable framework for unsupervised low, very low and extreme birth weight detection.
Published 2025-01-01“…This study presents an efficient and interpretable framework for unsupervised detection of low, very low, and extreme birth weights. …”
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On the non-parametric changepoint detection of flow regimes in cyclone Amphan
Published 2023-04-01“…This article explores the possibility of using a non-parametric algorithm to identify different flow regimes using a one-month long time-series data of the near-surface parameters. …”
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EMB-YOLO: A Lightweight Object Detection Algorithm for Isolation Switch State Detection
Published 2024-10-01Get full text
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