讨好美人
发表于 2025-3-23 09:55:14
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fluoroscopy
发表于 2025-3-23 15:09:16
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Texture
发表于 2025-3-23 19:27:11
Optimizing 3D UAV Path Planning: A Multi-strategy Enhanced Beluga Whale Optimizer a novel approach to address the problem by incorporating flight distance, threat cost, flight altitude and path smoothness constraints into a comprehensive cost function. The current popular metaheuristic algorithm is utilized to solve for the closest globally optimal UAV flight path. To overcome t
纺织品
发表于 2025-3-23 23:21:20
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SSRIS
发表于 2025-3-24 04:30:52
PatchFinger: A Model Fingerprinting Scheme Based on Adversarial Patcharking schemes based on backdoors require explicit embedding of the backdoor, which changes the structure and parameters. Model fingerprinting based on adversarial examples does not require any modification of the model, but is limited by the characteristics of the original task and not versatile en
oxidize
发表于 2025-3-24 09:28:43
Attribution of Adversarial Attacks via Multi-task Learninginal examples. Many works focus on adversarial detection and adversarial training to defend against adversarial attacks. However, few works explore the tool-chains behind adversarial examples, which is called Adversarial Attribution Problem (AAP). In this paper, AAP is defined as the recognition of
transplantation
发表于 2025-3-24 14:39:20
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GORGE
发表于 2025-3-24 15:07:04
A Novel Machine Learning Model Using CNN-LSTM Parallel Networks for Predicting Ship Fuel Consumptionsions for ships. This paper proposes a novel model of parallel network by combining convolutional neural network and long short-term memory (CNN-LSTM). The proposed model integrates three advantages. The CNN part of proposed model can extract spatial features, the LSTM part of proposed model can cap
GUMP
发表于 2025-3-24 20:09:34
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Unsaturated-Fat
发表于 2025-3-25 02:00:57
Learning Primitive-Aware Discriminative Representations for Few-Shot Learningome works about FSL have yielded promising classification performance, where the image-level feature is used to calculate the similarity among samples for classification. However, the image-level feature ignores abundant fine-grained and structural information of objects that could be transferable a