This research aims to create a smart residential system that will improve parking management in residential areas using mini-server technology. Another aim is to provide a safe and effective smart parking solution for...
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ISBN:
(数字)9798350375886
ISBN:
(纸本)9798350375893
This research aims to create a smart residential system that will improve parking management in residential areas using mini-server technology. Another aim is to provide a safe and effective smart parking solution for residential areas with limited capacity. This research method uses mini-server technology and control to create smart system ideas. Apart from that, this research also uses servo motor technology, proximity sensors, cameras, and IoT applications for smart parking management. The result is the creation of intelligent residential parking management, which uses a Raspberry Pi 5 Model B as a server and control to improve the parking management system in residential areas, and the use of number plate recognition technology to be applied to Smart City. This further research offers a new perspective on creating intelligent parking solutions using two input validation parameters simultaneously, namely facial and license plate recognition
Short Read Alignment Mapping Metrics (SRAMM): is an efficient and versatile command line tool providing additional short read mapping metrics, filtering, and graphs. Short read aligners report MAPing Quality (MAPQ), b...
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Contrastive learning-based video-language representation learning approaches, e.g., CLIP, have achieved outstanding performance, which pursue semantic interaction upon pre-defined video-text pairs. To clarify this coa...
Contrastive learning-based video-language representation learning approaches, e.g., CLIP, have achieved outstanding performance, which pursue semantic interaction upon pre-defined video-text pairs. To clarify this coarse-grained global interaction and move a step further, we have to encounter challenging shell-breaking interactions for fine-grained cross-modal learning. In this paper, we creatively model video-text as game players with multivariate cooperative game theory to wisely handle the uncertainty during fine-grained semantic interaction with diverse granularity, flexible combination, and vague intensity. Concretely, we propose Hierarchical Banzhaf Interaction (HBI) to value possible correspondence between video frames and text words for sensitive and explainable cross-modal contrast. To efficiently realize the cooperative game of multiple video frames and multiple text words, the proposed method clusters the original video frames (text words) and computes the Banzhaf Interaction between the merged tokens. By stacking token merge modules, we achieve cooperative games at different semantic levels. Extensive experiments on commonly used text-video retrieval and video-question answering bench-marks with superior performances justify the efficacy of our HBI. More encouragingly, it can also serve as a visualization tool to promote the understanding of cross-modal interaction, which have a far-reaching impact on the community. Project page is available at https://***/HBI/.
A novel method has been developed to evaluate the water diffusion dynamics in gelatin-based gels, based on transient terahertz time-domain spectroscopy measurements. Such gels are widely used models for human skin.
ISBN:
(纸本)9798350369311
A novel method has been developed to evaluate the water diffusion dynamics in gelatin-based gels, based on transient terahertz time-domain spectroscopy measurements. Such gels are widely used models for human skin.
Recently, self-supervised large-scale visual pre-training models have shown great promise in representing pixel-level semantic relationships, significantly promoting the development of unsupervised dense prediction ta...
Recently, self-supervised large-scale visual pre-training models have shown great promise in representing pixel-level semantic relationships, significantly promoting the development of unsupervised dense prediction tasks, e.g., unsupervised semantic segmentation (USS). The extracted relationship among pixel-level representations typically contains rich class-aware information that semantically identical pixel embeddings in the representation space gather together to form sophisticated concepts. However, leveraging the learned models to ascertain semantically consistent pixel groups or regions in the image is non-trivial since over/ under-clustering overwhelms the conceptualization procedure under various semantic distributions of different images. In this work, we investigate the pixel-level semantic aggregation in self-supervised ViT pre-trained models as image Segmentation and propose the Adaptive Conceptualization approach for USS, termed ACSeg. Concretely, we explicitly encode concepts into learnable prototypes and design the Adaptive Concept Generator (ACG), which adaptively maps these prototypes to informative concepts for each image. Meanwhile, considering the scene complexity of different images, we propose the modularity loss to optimize ACG independent of the concept number based on estimating the intensity of pixel pairs belonging to the same concept. Finally, we turn the USS task into classifying the discovered concepts in an unsupervised manner. Extensive experiments with state-of-the-art results demonstrate the effectiveness of the proposed ACSeg.
We present results for the axial charge and root-mean-square (RMS) radii of the nucleon obtained from 2+1 flavor lattice QCD at the physical point with a large spatial extent of about 10 fm. Our calculations are perfo...
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Driven by advances in generative artificial intelligence (AI) techniques and algorithms, the widespread adoption of AI-generated content (AIGC) has emerged, allowing for the generation of diverse and high-quality cont...
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A nanophotonic waveguide coupled with an atomic array forms one of the strongly-coupled quantum interfaces to showcase many fascinating collective features of quantum dynamics. In particular for a dissimilar array of ...
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Distinct selectivity to the spin angular momenta of photons have garnered significant attention in recent years, for their relevance in basic science and for imaging and sensing applications. While nonlocal metasurfac...
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The government in Indonesia and its staff work together to make tactical steps to prevent the spread of COVID-19 in the community. From the ministerial level to the heads of the provinces, regencies, and even the gove...
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