Large-scale neural networks-based federated learning(FL)has gained public recognition for its effective capabilities in distributed ***,the open system architecture inherent to federated learning systems raises concer...
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Large-scale neural networks-based federated learning(FL)has gained public recognition for its effective capabilities in distributed ***,the open system architecture inherent to federated learning systems raises concerns regarding their vulnerability to potential *** attacks turn into a major menace to federated learning on account of their concealed property and potent destructive *** altering the local model during routine machine learning training,attackers can easily contaminate the global *** detection and aggregation solutions mitigate certain threats,but they are still insufficient to completely eliminate the influence generated by ***,federated unlearning that can remove unreliable models while maintaining the accuracy of the global model has become a *** some existing federated unlearning approaches are rather difficult to be applied in large neural network models because of their high computational ***,we propose SlideFU,an efficient anti-poisoning attack federated unlearning *** primary concept of SlideFU is to employ sliding window to construct the training process,where all operations are confined within the *** design a malicious detection scheme based on principal component analysis(PCA),which calculates the trust factors between compressed models in a low-cost way to eliminate unreliable *** confirming that the global model is under attack,the system activates the federated unlearning process,calibrates the gradients based on the updated direction of the calibration *** on two public datasets demonstrate that our scheme can recover a robust model with extremely high efficiency.
High reliability applications in dense access scenarios have become one of the main goals of 6G *** solve the access collision of dense Machine Type communication(MTC)devices in cell-free communication systems,an inte...
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High reliability applications in dense access scenarios have become one of the main goals of 6G *** solve the access collision of dense Machine Type communication(MTC)devices in cell-free communication systems,an intelligent cooperative secure access scheme based on multi-agent reinforcement learning and federated learning is proposed,that is,the Preamble Slice Orderly Queue Access(PSOQA)*** this scheme,the preamble arrangement is combined with the access *** preamble arrangement is realized by preamble slices which is from the virtual preamble *** access devices learn to queue orderly by deep reinforcement *** orderly queue weakens the random and avoids collision.A preamble slice is assigned to an orderly access queue at each access *** orderly queue is determined by interaction information among multiple *** the federated reinforcement learning framework,the PSOQA scheme is implemented to guarantee the privacy and security of ***,the access performance of PSOQA is compared with other random contention schemes in different load *** results show that PSOQA can not only improve the access success rate but also guarantee low-latency tolerant performances.
Referring Video Object Segmentation (RVOS) aims at segmenting out the described object in a video clip according to given expression. The task requires methods to effectively fuse cross-modality features, communicate ...
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The global expansion of multimedia data over the internet has led to a new revolution. Multimedia data, especially medical records, are to be dealt with utmost security for telemedicine applications. This paper presen...
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Enhancement of a low-contrast image is an essential and challenging task in any computer vision-related application. Perceptually invisible images and the images captured by low dynamic range devices are poor in contr...
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The study examines ESP32-based static and dynamic load-balancing algorithms to enhance defence networks’ Wi-Fi range and traffic control. This study is essential due to the growing need for dependable and efficient w...
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This paper presents a saliency and contrast mapping-based enhancement technique for dark images with web application. The dark images are not favorable to computer vision systems and human observations because of thei...
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The development of artificial intelligence(AI)technologies creates a great chance for the iteration of railway *** paper proposes a comprehensive method for railway utility pole *** framework of this paper on railway ...
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The development of artificial intelligence(AI)technologies creates a great chance for the iteration of railway *** paper proposes a comprehensive method for railway utility pole *** framework of this paper on railway systems consists of two parts:point cloud preprocessing and railway utility pole *** overcomes the challenges of dynamic environment adaptability,reliance on lighting conditions,sensitivity to weather and environmental conditions,and visual occlusion issues present in 2D images and videos,which utilize mobile LiDAR(Laser Radar)acquisition devices to obtain point cloud *** to factors such as acquisition equipment and environmental conditions,there is a significant amount of noise interference in the point cloud data,affecting subsequent detection *** designed a Dual-Region Adaptive Point Cloud Preprocessing method,which divides the railway point cloud data into track and non-track *** track region undergoes projection dimensionality reduction,with the projected results being unique and subsequently subjected to 2D density clustering,greatly reducing data computation *** non-track region undergoes PCA-based dimensionality reduction and clustering operations to achieve preprocessing of large-scale point cloud ***,the preprocessed results are used for training,achieving higher accuracy in utility pole detection and data *** results show that our proposed preprocessing method not only improves efficiency but also enhances detection accuracy.
In the last decade, the prevalence of diabetic retinopathy (DR), a sight-threatening medical condition of diabetes mellitus, has markedly increased, impacting millions globally. The conventional method of diagnosing a...
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Intelligent video surveillance systems with anomaly detection capabilities are indispensable for outdoor security. Video anomaly detection (VAD) is usually performed by learning patterns representing normal events and...
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