This study presents a deep learning framework optimizing 3D clothing models for VR, using a CNN to significantly reduce the triangle count of models from DeepFashion3D and CAP-UDF datasets. Achieving a balance between...
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ISBN:
(数字)9798350386844
ISBN:
(纸本)9798350386851
This study presents a deep learning framework optimizing 3D clothing models for VR, using a CNN to significantly reduce the triangle count of models from DeepFashion3D and CAP-UDF datasets. Achieving a balance between efficiency and detail, it cuts triangle count from over 160,000 to below 4,000, maintaining high DPI. The approach automates optimization, promising scalability and efficiency in VR fashion, setting a foundation for future 3D content development, enhancing virtual garment realism and interactivity.
This paper considers video and audio transmission in ICN (Information-Centric Networking)/ CCN (ContentCentric Networking), where each intermediate node can cache content. We have proposed LCD with Prob, combining tra...
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ISBN:
(数字)9798350309485
ISBN:
(纸本)9798350309492
This paper considers video and audio transmission in ICN (Information-Centric Networking)/ CCN (ContentCentric Networking), where each intermediate node can cache content. We have proposed LCD with Prob, combining traditional policies: LCD (Leave Copy Down) and probabilistic caching. This paper assumes a case where multiple video and audio streams exist simultaneously. We assess application-level QoS (Quality of Service) and QoE (Quality of Experience) of video and audio transmission utilizing LCD with Prob. We also add a mechanism for further QoE enhancement called “LCD with Prob deletion.” We assess application-level QoS using a computer simulation with a tree network and QoE by means of a subjective experiment. From the assessment result, we show the effectiveness of LCD with Prob deletion against existing policies.
In an attempt to bridge the semantic gap between language understanding and visuals, Visual Question Answering (VQA) offers a challenging intersection of computer vision and natural language processing. Large Language...
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ISBN:
(数字)9798350362633
ISBN:
(纸本)9798350362640
In an attempt to bridge the semantic gap between language understanding and visuals, Visual Question Answering (VQA) offers a challenging intersection of computer vision and natural language processing. Large Language Models (LLMs) have shown remarkable ability in natural language understanding; however, their use in VQA, particularly for Arabic, is still largely unexplored. This study aims to bridge this gap by examining how well LLMs can improve VQA models. We use state-of-the-art AI algorithms on datasets from multiple fields, including electric devices, Visual Genome, RSVQA, and ChartsQA. We introduce ArabicQuest, a Text Question Answering (TQA) tool that combines Arabic inquiries with visual data. We assess the performance of LLMs across various question types and image settings and find that fine-tuning me thods su ch as LLaMA-2, BLIP-2, and Idefics-9B-Instruct models provide encouraging results, although challenges still arise in counting and comparison tasks. Our findings demonstrate the importance of advancing VQA further—especially for Arabic—to enhance accessibility and user satisfaction in a variety of applications.
computer vision has emerged as an important subject of study, with several practical applications in a wide range of domains. OpenCV, a widely used framework, has played an important role in allowing computer vision t...
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This paper compares video and audio QoE of OFDMA multi-user transmission and reliable groupcast over wireless LAN. We assume video and audio transmission to several terminals simultaneously. As a reliable groupcast me...
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ISBN:
(数字)9798350364866
ISBN:
(纸本)9798350364873
This paper compares video and audio QoE of OFDMA multi-user transmission and reliable groupcast over wireless LAN. We assume video and audio transmission to several terminals simultaneously. As a reliable groupcast method, we employ Unsolicited Retry, a technique of IEEE 802.11aa GroupCast with Retries. We utilize IEEE 802.11ax for OFDMA transmission. We evaluate application-level QoS by computer simulation. We then assess QoE through a subjective experiment with video and audio streams generated by the output timing obtained from the simulation. We notice that each method has a situation to be applied appropriately.
Symmetric algorithms offer speed but have weaknesses in key distribution, while asymmetric algorithms are secure but less efficient for encrypting and decrypting large text messages. This research aims to secure data ...
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ISBN:
(数字)9798331531249
ISBN:
(纸本)9798331531256
Symmetric algorithms offer speed but have weaknesses in key distribution, while asymmetric algorithms are secure but less efficient for encrypting and decrypting large text messages. This research aims to secure data and digital documents through the implementation of a hybrid cryptosystem that combines the Cramer-Shoup algorithm and Spritz. This research also analyzes and evaluates the effectiveness and speed of encryption and decryption, as well as the efficiency of the system in protecting various types of data, including docx and pdf document files. The methodology of this research includes a literature review, analysis of the encryption-decryption process, and performance testing of the system using the Python programming language. The speed test results show that this hybrid cryptosystem provides fast encryption-decryption times, with an encryption time of 0.002607 milliseconds for 400 characters and a decryption time of 0.001537 milliseconds, while for digital documents of the pdf file type, the encryption time is 0.424478 milliseconds and the decryption time is 0.404343 milliseconds. In addition, the use of the SHA-3 hash function has proven effective in maintaining data integrity. In conclusion, this hybrid cryptosystem offers an efficient and secure solution for protecting various types of digital data, including text and documents.
In the context of smart cities where green infras-tructure is incentived, besides important benefits like regulating temperatures and absorbing pollutants among others, tour by urban forests is a way to experience clo...
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In this paper, we consider multi-view video and audio streaming using MPEG-DASH, which enables to transmit video tailored to the network conditions over HTTP communication. This paper uses HTTP/2 instead of HTTP/1.1, ...
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ISBN:
(数字)9798350353983
ISBN:
(纸本)9798350353990
In this paper, we consider multi-view video and audio streaming using MPEG-DASH, which enables to transmit video tailored to the network conditions over HTTP communication. This paper uses HTTP/2 instead of HTTP/1.1, which the authors previously used. HTTP/2 manages a series of request-response exchanges called a stream, which is assigned a unique stream ID. We perform a subjective experiment under various network conditions to evaluate application-level QoS and QoE. From the evaluation results, we investigate the effect of the HTTP/2 stream on the video and audio quality of the users in the multi-view video transmission scenario.
This paper considers multi-view video and audio transmission on ICN (Information-Centric Networking)/CCN (Content-Centric Networking). Routers in ICN/CCN can cache content. Besides, the capacity of routers' caches...
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ISBN:
(数字)9798350374537
ISBN:
(纸本)9798350374544
This paper considers multi-view video and audio transmission on ICN (Information-Centric Networking)/CCN (Content-Centric Networking). Routers in ICN/CCN can cache content. Besides, the capacity of routers' caches is finite, so various cache control schemes have been proposed to improve cache efficiency. This paper presents and evaluates a new and suitable control scheme for multi-view video and audio transmission. For this purpose, we construct a network environment with Cefore. We assess application-level QoS (Quality of Service) and QoE (Quality of Experience). We then show the effectiveness of the proposed control scheme.
作者:
Janet Van NiekerkHåvard RueStatistics Program
Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal Kingdom of Saudi Arabia
Approximate inference methods like the Laplace method, Laplace approximations and variational methods, amongst others, are popular methods when exact inference is not feasible due to the complexity of the model or the...
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Approximate inference methods like the Laplace method, Laplace approximations and variational methods, amongst others, are popular methods when exact inference is not feasible due to the complexity of the model or the abundance of data. In this paper we propose a hybrid approximate method called Low-Rank Variational Bayes correction (VBC), that uses the Laplace method and subsequently a Variational Bayes correction in a lower dimension, to the joint posterior mean. The cost is essentially that of the Laplace method which ensures scalability of the method, in both model complexity and data size. Models with fixed and unknown hyperparameters are considered, for simulated and real examples, for small and large data sets.
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