Facial expression recognition is a challenging task when neural network is applied to pattern recognition. Most of the current recognition research is based on single source facial data, which generally has the disadv...
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The surrounding environmental and climatic conditions have a significant impact on the utilisation of ecosystem services for recreational purposes. Climate change poses a threat to future natural leisure opportunities...
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Since most multiobjective optimization problems in real-world applications contain constraints, constraint-handling techniques (CHTs) are necessary for a multiobjective optimizer. However, existing CHTs give no relaxa...
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This paper presents BC-SBOM, a novel blockchainbased system designed to enhance the management of Software Bills of Materials (SBOMs). By leveraging blockchain technology, BC-SBOM ensures secure storage and sharing of...
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ISBN:
(纸本)9791188428137
This paper presents BC-SBOM, a novel blockchainbased system designed to enhance the management of Software Bills of Materials (SBOMs). By leveraging blockchain technology, BC-SBOM ensures secure storage and sharing of SBOMs, while providing a comprehensive global view of dependencies among software components. The system also supports rapid propagation of alerts for newly discovered vulnerabilities, thereby increasing responsiveness to potential threats. Offering superior reliability, transparency, and availability compared to traditional SBOM tools, BC-SBOM aims to significantly improve the management of complex software systems and contribute to the advancement of software security practices. Copyright 2025 Global IT Research Institute (GIRI). All rights reserved.
Major deaths (55% or 1.5 million) of LRI (Lower Respiratory Infections) are caused due to Pneumococcal pneumonia. LRI is the 5th highest cause of demise as mentioned by the Global Burden of Disease Study 2015. Health ...
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In healthcare, remote sensing technologies are popular for smart patient health monitoring. Real-time health assessment and early intervention are possible using remote sensing data from wearable sensors and imaging e...
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Image-text retrieval aims to capture the semantic correspondence between images and texts,which serves as a foundation and crucial component in multi-modal recommendations,search systems,and online *** mainstream meth...
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Image-text retrieval aims to capture the semantic correspondence between images and texts,which serves as a foundation and crucial component in multi-modal recommendations,search systems,and online *** mainstream methods primarily focus on modeling the association of image-text pairs while neglecting the advantageous impact of multi-task learning on image-text *** this end,a multi-task visual semantic embedding network(MVSEN)is proposed for image-text ***,we design two auxiliary tasks,including text-text matching and multi-label classification,for semantic constraints to improve the generalization and robustness of visual semantic embedding from a training ***,we present an intra-and inter-modality interaction scheme to learn discriminative visual and textual feature representations by facilitating information flow within and between ***,we utilize multi-layer graph convolutional networks in a cascading manner to infer the correlation of image-text *** results show that MVSEN outperforms state-of-the-art methods on two publicly available datasets,Flickr30K and MSCOCO,with rSum improvements of 8.2%and 3.0%,respectively.
This research focuses on improving maritime ob-ject detection by refining deep neural network models with the Roboflow ship detection dataset, which contains labeled images of ships. The main goal is to assess the per...
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This article defines embeddings between state-based and action-based probabilistic logics which can be used to support probabilistic model checking. First, we slightly modify the model embeddings proposed in the liter...
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Machine learning techniques have become ubiquitous both in industry and academic *** model sizes and training data volumes necessitate fast and efficient distributed training *** communications greatly simplify inter-...
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Machine learning techniques have become ubiquitous both in industry and academic *** model sizes and training data volumes necessitate fast and efficient distributed training *** communications greatly simplify inter-and intra-node data transfer and are an essential part of the distributed training process as information such as gradients must be shared between processing *** this paper,we survey the current state-of-the-art collective communication libraries(namely xCCL,including NCCL,oneCCL,RCCL,MSCCL,ACCL,and Gloo),with a focus on the industry-led ones for deep learning *** investigate the design features of these xCCLs,discuss their use cases in the industry deep learning workloads,compare their performance with industry-made benchmarks(i.e.,NCCL Tests and PARAM),and discuss key take-aways and interesting *** believe our survey sheds light on potential research directions of future designs for xCCLs.
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