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Lip Feature Disentanglement for Visual Speaker Authentication in Natural Scenes
Recent studies have shown that lip shape and movement can be used as an effective biometric feature for speaker authentication. By …
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Lip Feature Disentanglement for Visual Speaker Authentication in Natural Scenes
自然语言处理中的探针可解释方法综述
随着大规模预训练模型的广泛应用，自然语言处理的各领域（如文本分类和机器翻译）均取得了长足的发展。然而，受限于预训练模型的“黑盒”特性，其内部的决策模式以及编码的知识信息被认为是不透明的。以OpenAI发布的ChatGPT和GPT-4为代表的先进预训练模型为例，它们在各领 …
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自然语言处理中的探针可解释方法综述
Fine-Grained Lip Image Segmentation using Fuzzy Logic and Graph Reasoning
Fine-grained lip image segmentation plays a critical role in downstream tasks such as automatic lipreading, as it enables the accurate …
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Fine-Grained Lip Image Segmentation using Fuzzy Logic and Graph Reasoning
Linear Functionality Equivalence Attack against Deep Neural Network Watermarks and a Defense Method by Neuron Mapping
As an ownership verification technique for deep neural networks, the white-box neural network watermark is being challenged by the …
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Linear Functionality Equivalence Attack against Deep Neural Network Watermarks and a Defense Method by Neuron Mapping
Exploiting Complementary Dynamic Incoherence for DeepFake Video Detection
Recently, manipulated videos based on DeepFake technology have spread widely on social media, causing concerns about the authenticity …
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Exploiting Complementary Dynamic Incoherence for DeepFake Video Detection
DESC-IDS: Towards an Efficient Real-time Automotive Intrusion Detection System Based on Deep Evolving Stream Clustering
Controller area network (CAN) is a widely used communication protocol for in-vehicle networks. With the up-gradation of traditional …
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DESC-IDS: Towards an Efficient Real-time Automotive Intrusion Detection System Based on Deep Evolving Stream Clustering
Online Intrusion Detection for IoT Systems with Full Bayesian Possibilistic Clustering and Ensembled Fuzzy Classifiers
The pervasive deployment of the internet of things (IoT) has significantly facilitated manufacturing and living. The diversity and …
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Online Intrusion Detection for IoT Systems with Full Bayesian Possibilistic Clustering and Ensembled Fuzzy Classifiers