Video anomaly detection (VAD) is a crucial task in video analysis and surveillance within computer vision. Currently, VAD is gaining attention with memory techniques that store the features of normal frames. The store...
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Biology today is heavily data-driven and knowledge-centric that are stored across the linked open web in numerous heterogeneous deep web databases. To improve searching, finding, accessing, and inter-operating among t...
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We propose a novel single-view human body 3D reconstruction framework guided by the semantic field. We argue that the full visibility of 2D human shape and the alignment between geometric and semantic features are vit...
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In the rapidly evolving landscape of Software-Defined Networks (SDNs), mitigating Distributed Denial of Service (DDoS) attacks presents significant security challenges. This paper introduces a sensor-enhanced hybrid a...
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This paper explores the use of Large Language Models (LLMs) to transform SEO practices in digital marketing. By leveraging LLM capabilities, the study enhances content creation, keyword research, meta descriptions, an...
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The earlier research clearly indicated that the bimodal authentication system has more efficiency than unimodal and multimodal. This is due to the reason for the best intact biometric traits of fingerprint and retina....
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A key component of managing natural resources is the use and cover of the land. Maps of environmental changes are created using it in order to monitor ecosystems. For forestry, urban planning and agriculture, automati...
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Diabetic retinopathy, a condition characterized by retinal damage and vision loss, is a prevalent complication of diabetes arising from elevated blood sugar levels. With a growing number of individuals affected, effic...
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Facial beauty analysis is an important topic in human *** may be used as a guidance for face beautification applications such as cosmetic *** neural networks(DNNs)have recently been adopted for facial beauty analysis ...
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Facial beauty analysis is an important topic in human *** may be used as a guidance for face beautification applications such as cosmetic *** neural networks(DNNs)have recently been adopted for facial beauty analysis and have achieved remarkable ***,most existing DNN-based models regard facial beauty analysis as a normal classification *** ignore important prior knowledge in traditional machine learning models which illustrate the significant contribution of the geometric features in facial beauty *** be specific,landmarks of the whole face and facial organs are introduced to extract geometric features to make the *** by this,we introduce a novel dual-branch network for facial beauty analysis:one branch takes the Swin Transformer as the backbone to model the full face and global patterns,and another branch focuses on the masked facial organs with the residual network to model the local patterns of certain facial ***,the designed multi-scale feature fusion module can further facilitate our network to learn complementary semantic information between the two *** model optimisation,we propose a hybrid loss function,where especially geometric regulation is introduced by regressing the facial landmarks and it can force the extracted features to convey facial geometric *** performed on the SCUT-FBP5500 dataset and the SCUT-FBP dataset demonstrate that our model outperforms the state-of-the-art convolutional neural networks models,which proves the effectiveness of the proposed geometric regularisation and dual-branch structure with the hybrid *** the best of our knowledge,this is the first study to introduce a Vision Transformer into the facial beauty analysis task.
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