Current software development has moved away from the traditional manual workshop model and emphasizes improving software product quality. To address the issue of repetitive work, software reuse techniques can be adopt...
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This present work describes a framework for the analysis of score dynamics and energy fluctuations in competitive environments, aimed at forecasting match outcomes and providing strategic decisions useful to coaching ...
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As software demand proliferates and software size and complexity increase, traditional software development models face enormous challenges. As a result, new software development techniques are being explored to meet ...
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Due to their biological interpretability,memristors are widely used to simulate synapses between artificial neural *** a type of neural network whose dynamic behavior can be explained,the coupling of resonant tunnelin...
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Due to their biological interpretability,memristors are widely used to simulate synapses between artificial neural *** a type of neural network whose dynamic behavior can be explained,the coupling of resonant tunneling diode-based cellular neural networks(RTD-CNNs)with memristors has rarely been reported in the ***,this paper designs a coupled RTD-CNN model with memristors(RTD-MCNN),investigating and analyzing the dynamic behavior of the *** on this model,a simple encryption scheme for the protection of digital images in police forensic applications is *** results show that the RTD-MCNN can have two positive Lyapunov exponents,and its output is influenced by the initial values,exhibiting ***,a set of amplitudes in its output sequence is affected by the internal parameters of the memristor,leading to nonlinear ***,the rich dynamic behaviors described above make the RTD-MCNN highly suitable for the design of chaos-based encryption schemes in the field of privacy *** tests and security analyses validate the effectiveness of this scheme.
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.
In recent years, the increasing number of individuals diagnosed with depression and the growing awareness of its impact on modern society have highlighted the significance of accurate depression diagnosis. Microarray ...
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Lesion detection in Computed Tomography(CT) images is a challenging task in the field of computer-aided *** important issue is to locate the area of lesion *** a branch of Convolutional Neural Networks(CNNs),3D Contex...
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Lesion detection in Computed Tomography(CT) images is a challenging task in the field of computer-aided *** important issue is to locate the area of lesion *** a branch of Convolutional Neural Networks(CNNs),3D Context-Enhanced(3DCE) frameworks are designed to detect lesions on CT *** False Positives(FPs) detected in 3DCE frameworks are usually caused by inaccurate region proposals,which slow down the inference *** solve the above problems,a new method is proposed,a dimension-decomposition region proposal network is integrated into 3DCE framework to improve the location accuracy in lesion *** the restriction of "anchors" on ratios and scales,anchors are decomposed to independent "anchor strings".Anchor segments are dynamically combined in accordance with probability,and anchor strings with different lengths dynamically compose bounding *** show that the accurate region proposals generated by our model promote the sensitivity of FPs and spend less inference time compared with the current methods.
Pedestrian re-identification technology enables accurate identification of individuals and is widely used in modern intelligent video surveillance systems to aid law enforcement, including criminal apprehension and lo...
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Person Re-Identification falls within the scope of computer vision, acting a technique to ascertain the presence of a specified pedestrian within a video or image library. The related research is of great significance...
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In Currently, research in the field of infrared road object detection is primarily focused on enhancing model performance and robustness to address the challenges posed by complex real-world driving scenarios. In resp...
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