Zobrazeno 1 - 10
of 3 391
pro vyhledávání: '"Image inpainting"'
Publikováno v:
IET Image Processing, Vol 18, Iss 12, Pp 3343-3355 (2024)
Abstract In recent years, deep learning models have dramatically influenced image inpainting. However, many existing studies still suffer from over‐smoothed or blurred textures when missing regions are large or contain rich visual details. To resto
Externí odkaz:
https://doaj.org/article/0da85b4d2d2c438f9576de894c9e42ec
Autor:
Yongqin Zhang, Xiaoyu Wang, Panpan Zhu, Xuan Lu, Jinsheng Xiao, Wei Zhou, Zhan Li, Xianlin Peng
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-14 (2024)
Abstract Ancient murals embody profound historical, cultural, scientific, and artistic values, yet many are afflicted with challenges such as pigment shedding or missing parts. While deep learning-based completion techniques have yielded remarkable r
Externí odkaz:
https://doaj.org/article/7945937bae404ebd853c238f879bbc7b
Publikováno v:
Visual Informatics, Vol 8, Iss 3, Pp 71-81 (2024)
Existing lip synchronization (lip-sync) methods generate accurately synchronized mouths and faces in a generated video. However, they still confront the problem of artifacts in regions of non-interest (RONI), e.g., background and other parts of a fac
Externí odkaz:
https://doaj.org/article/1bfe790beda3418982074c89238f1d8b
Publikováno v:
Alexandria Engineering Journal, Vol 111, Iss , Pp 511-520 (2025)
Ancient murals, as invaluable cultural artifacts, have profound historical and cultural significance. However, these murals often face degradation phenomena such as peeling, fading, and cracking, which compromises their preservation. Conventional met
Externí odkaz:
https://doaj.org/article/40d417e9c81b4ba3b013558d23a1acd5
Autor:
Akmal Shafiq Badarul Azam, Abdul Kadir Jumaat, Amisha Balkis Badarul Azam, Nur Afiqah Sabirah Mohammad Sabri, Amiratul Munirah Yahaya, Ahmad Thaqif Ismail, Muhammad Anas Abdul Razak, Mohd Azdi Maasar, Mohamed Faris Laham
Publikováno v:
Journal of ICT, Vol 23, Iss 4 (2024)
Old Jawi Manuscripts (OJM) are crucial to historical studies, offering insights into past societies. However, degradation from mishandling and environmental factors can impair their legibility. To preserve OJM, image inpainting and segmentation are e
Externí odkaz:
https://doaj.org/article/36a5fccad99b4808ad4c32cc719a7c18
Autor:
Poonam L Rakibe, Pramod D Patil
Publikováno v:
e-Prime: Advances in Electrical Engineering, Electronics and Energy, Vol 9, Iss , Pp 100678- (2024)
Distorted medical images can drastically reduce diagnosis accuracy using computer-aided diagnostic (CAD) systems. The objective of medical image classification is to improve diagnostic imaging precision and restore regions degraded by image inpaintin
Externí odkaz:
https://doaj.org/article/04ef2c04f697443fa929865697978fd9
Publikováno v:
Complex & Intelligent Systems, Vol 10, Iss 4, Pp 4921-4938 (2024)
Abstract The integration of convolutional neural network (CNN) and transformer enhances the network’s capacity for concurrent modeling of texture details and global structures. However, training challenges with transformer limit their effectiveness
Externí odkaz:
https://doaj.org/article/da6edae82f864f62933ca99c3bd8cb73
Publikováno v:
Jisuanji kexue yu tansuo, Vol 18, Iss 3, Pp 553-573 (2024)
With the rapid development of generative adversarial networks, many image restoration problems that are difficult to solve based on traditional methods have gained new research approaches. With its powerful generation ability, generative adversarial
Externí odkaz:
https://doaj.org/article/1317aaf95c184146b258da775ba315ac
Publikováno v:
IET Image Processing, Vol 18, Iss 2, Pp 428-438 (2024)
Abstract Image inpainting networks based on deep learning techniques have been widely used in many important fields. However, most inpainting networks fail to generate desirable repaired images. This may be due to their failure to extract effective f
Externí odkaz:
https://doaj.org/article/8789288d2bd542d9a75d03ff5a18e4d6