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Jarina Raihan Ahamed, Pg Emeroylariffion Abas, Liyanage Chandratilak De Silva
Pág. 195 - 205
The objective of this study is to convert normal aerial images into underwater images based on attenuation values for different water types by utilizing the image formation model (IFM) with Jerlov water types. Firstly, the depth values are derived from R...
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Zhiqiang Zhang, Chen Fu, Wei Weng and Jinjia Zhou
Due to the high flexibility and conformity to people?s usage habits, text description has been widely used in image synthesis research recently and has achieved many encouraging results. However, the text can only determine the basic content of the gener...
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Thai Leang Sung and Hyo Jong Lee
We propose Identical-pair Adversarial Networks (iPANs) to solve image-to-image translation problems, such as aerial-to-map, edge-to-photo, de-raining, and night-to-daytime. Our iPANs rely mainly on the effectiveness of adversarial loss function and its n...
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Xuanyuan Xie and Jieyu Zhao
The diffusion model has made progress in the field of image synthesis, especially in the area of conditional image synthesis. However, this improvement is highly dependent on large annotated datasets. To tackle this challenge, we present the Guided Diffu...
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Shun Liu, Hongyi Lu, Bin Zhang, Yucheng Yang and Doudou Sang
The presence of the erosive burning effect during the operation of a solid rocket motor (SRM) is one of the most important factors affecting the proper operation of the motor. To solve the effects of the operating process of the motor under erosive burni...
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Qianmu Xiao and Liang Zhao
Acquiring relevant, high-quality, and heterogeneous medical images is essential in various types of automated analysis, used for a variety of downstream data augmentation tasks. However, a large number of real image samples are expensive to obtain, espec...
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Marco Seracini and Stephen R. Brown
In this article, we introduce a new mathematical functional whose minimization determines the quality of the solution for the exemplar-based inpainting-by-patch problem. The new functional expression includes finite difference terms in a similar fashion ...
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Yi-Quan Li, Hao-Sen Chang and Daw-Tung Lin
In the field of computer vision, large-scale image classification tasks are both important and highly challenging. With the ongoing advances in deep learning and optical character recognition (OCR) technologies, neural networks designed to perform large-...
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Daniele Passaretti, Mukesh Ghosh, Shiras Abdurahman, Micaela Lambru Egito and Thilo Pionteck
In computed tomography imaging, the computationally intensive tasks are the pre-processing of 2D detector data to generate total attenuation or line integral projections and the reconstruction of the 3D volume from the projections. This paper proposes th...
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Ulrike Faltings, Tobias Bettinger, Swen Barth and Michael Schäfer
Collecting and labeling of good balanced training data are usually very difficult and challenging under real conditions. In addition to classic modeling methods, Generative Adversarial Networks (GANs) offer a powerful possibility to generate synthetic tr...
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Jaehyun Lee, Jahanzeb Hafeez, Kwangjib Kim, Seunghyun Lee and Soonchul Kwon
With the advancement of media and computing technologies, video compositing techniques have improved to a great extent. These techniques have been used not only in the entertainment industry but also in advertisement and new media. Match-moving is a cine...
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Cheng-Bin Jin, Hakil Kim, Mingjie Liu, In Ho Han, Jae Il Lee, Jung Hwan Lee, Seongsu Joo, Eunsik Park, Young Saem Ahn and Xuenan Cui
Magnetic resonance imaging (MRI) plays a significant role in the diagnosis of lumbar disc disease. However, the use of MRI is limited because of its high cost and significant operating and processing time. More importantly, MRI is contraindicated for som...
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Maryam Omar, Hafeez Ur Rehman, Omar Bin Samin, Moutaz Alazab, Gianfranco Politano and Alfredo Benso
Text-to-image synthesis is one of the most critical and challenging problems of generative modeling. It is of substantial importance in the area of automatic learning, especially for image creation, modification, analysis and optimization. A number of wo...
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Uddom Lee, Peng Jiang, Hongyi Wu and Chunsheng Xin
Image-based localization has been widely used for autonomous vehicles, robotics, augmented reality, etc., and this is carried out by matching a query image taken from a cell phone or vehicle dashcam to a large scale of geo-tagged reference images, such a...
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Hyeon Kang, Jang-Sik Park, Kook Cho and Do-Young Kang
Conventional data augmentation (DA) techniques, which have been used to improve the performance of predictive models with a lack of balanced training data sets, entail an effort to define the proper repeating operation (e.g., rotation and mirroring) acco...
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Dong-Min Son, Hyuk-Ju Kwon and Sung-Hak Lee
This study proposes a method of blending visible and near-infrared (NIR) images to enhance their edge details and local contrast based on the Laplacian pyramid and principal component analysis (PCA). In the proposed method, both the Laplacian pyramid and...
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Paidamwoyo Mhangara, Willard Mapurisa and Naledzani Mudau
High resolution pansharpened images are used for detailed land use and land cover mapping.
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Oleg O. Kartashov, Sergey V. Chapek, Dmitry S. Polyanichenko, Grigory I. Belyavsky, Alexander A. Alexandrov, Maria A. Butakova and Alexander V. Soldatov
Microfluidic devices have opened new opportunities for functional material chemical synthesis in a few applications. The screening of microfluidic synthesis processes is an urgent task of the experimental process in terms of automation and intellectualiz...
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Zengming Deng and Mingjiang Wang
View synthesis is a crucial technique for free viewpoint video and multi-view video coding because of its capability to render an unlimited number of virtual viewpoints from adjacent captured texture images and corresponding depth maps. The accuracy of d...
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Zhaoyang Liu, Renxiang Guan, Jingyu Hu, Weitao Chen and Xianju Li
Classification of remote sensing scene image (RSSI) has been broadly applied and has attracted increasing attention. However, scene classification methods based on convolutional neural networks (CNNs) require a large number of manually labeled samples as...
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