Existing learning models partition the generated representations using hyperplanes which form well defined groups of similar embeddings that is uniquely mapped to a particular class. However, in practical applications...
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The ubiquity of handheld devices and easy access to the Internet help users get easy and quick updates from social media. Generally, people share information with their friends and groups without inspecting the posts...
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Omnidirectional images provide an immersive viewing experience in a Virtual Reality (VR) environment, surpassing the limitations of traditional 2D media beyond the conventional screen. This VR technology allows users ...
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Omnidirectional images provide an immersive viewing experience in a Virtual Reality (VR) environment, surpassing the limitations of traditional 2D media beyond the conventional screen. This VR technology allows users to interact with visual information in an exciting and engaging manner. However, the storage and transmission requirements for 360-degree panoramic images are substantial, leading to the establishment of compression frameworks. Unfortunately, these frameworks introduce projection distortion and compression artifacts. With the rapid growth of VR applications, it becomes crucial to investigate the quality of the perceptible omnidirectional experience and evaluate the extent of visual degradation caused by compression. In this regard, viewport plays a significant role in omnidirectional image quality assessment (OIQA), as it directly affects the user’s perceived quality and overall viewing experience. Extracting viewports compatible with users viewing behavior plays a crucial role in OIQA. Different users may focus on different regions, and the model’s performance may be sensitive to the chosen viewport extraction strategy. Improper selection of viewports could lead to biased quality predictions. Instead of assessing the entire image, attention can be directed to areas that are more importance to the overall quality. Feature extraction is vital in OIQA as it plays a significant role in representing image content that aligns with human perception. Taking this into consideration, the proposed ATtention enabled VIewport Selection (ATVIS-OIQA) employs attention based view port selection with Vision Transformers(ViT) for feature extraction. Furthermore, the spatial relationship between the viewports is established using graph convolution, enabling intuitive prediction of the objective visual quality of omnidirectional images. The effectiveness of the proposed model is demonstrated by achieving state-of-the-art results on publicly available benchmark datasets, n
Background: In the wake of escalating cyber threats and the indispensability of ro-bust network security mechanisms, it becomes crucial to understand the evolving landscape of cryptographic research. Recognizing the s...
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Generating financial reports from a piece of news is a challenging task due to the lack of sufficient background knowledge to effectively generate long financial reports. To address this issue, this article proposes a...
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In the times of advanced generative artificial intelligence, distinguishing truth from fallacy and deception has become a critical societal challenge. This research attempts to analyze the capabilities of large langua...
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The objective of style transfer is to maintain the content of an image while transferring the style of another ***,conventional methods face challenges in preserving facial features,especially in Korean portraits wher...
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The objective of style transfer is to maintain the content of an image while transferring the style of another ***,conventional methods face challenges in preserving facial features,especially in Korean portraits where elements like the“Gat”(a traditional Korean hat)are *** paper proposes a deep learning network designed to perform style transfer that includes the“Gat”while preserving the identity of the *** traditional style transfer techniques,the proposed method aims to preserve the texture,attire,and the“Gat”in the style image by employing image sharpening and face landmark,with the *** color,texture,and intensity were extracted differently based on the characteristics of each block and layer of the pre-trained VGG-16,and only the necessary elements during training were preserved using a facial landmark *** head area was presented using the eyebrow area to transfer the“Gat”.Furthermore,the identity of the face was retained,and style correlation was considered based on the Gram *** evaluate performance,we introduced a metric using PSNR and SSIM,with an emphasis on median values through new weightings for style transfer in Korean ***,we have conducted a survey that evaluated the content,style,and naturalness of the transferred results,and based on the assessment,we can confidently conclude that our method to maintain the integrity of content surpasses the previous *** approach,enriched by landmarks preservation and diverse loss functions,including those related to“Gat”,outperformed previous researches in facial identity preservation.
Agriculture is the primary source of food, fuel, and raw materials and is vital to any country’s economy. Farmers, the backbone of agriculture, primarily rely on instinct to determine what crops to plant in any given...
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The vast volume of redundant and irrelevant network traffic data poses significant hurdles for intrusion detection. Effective feature selection is crucial for eliminating irrelevant information. Presently, most filter...
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Quality degradation due to the compression and the transmission of images is a significant threat to multimedia applications. Blind image quality assessment (BIQA) is a principal technique to measure the distortion an...
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