Results 1 to 10 of about 43,961 (294)
A generative adversarial network with multiscale and attention mechanisms for underwater image enhancement [PDF]
Scientific ReportsUnderwater images collected are often of low clarity and suffer from severe color distortion due to the marine environment and Illumination conditions.
Liquan Zhao, Yuda Li, Tie Zhong
doaj +2 more sources
A Tunnel Crack Segmentation and Recognition Algorithm Using SPGD-and-Generative Adversarial Network Fusion [PDF]
SensorsIn order to improve the recognition ability of tunnel cracks in the UAV platform with a vision imaging system in the UAV platform with a vision imaging system, this paper proposes a tunnel crack segmentation algorithm using SPGD-and-generative ...
Wei Sun, Xiaohu Liu, Zhiyong Lei
doaj +2 more sources
Generative Adversarial Networks
2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT), 2023 Generative adversarial networks (GANs) have transformed machine learning and created new research and application areas. GANs are now used for data augmentation, picture, audio, text-to-image, and 3D object production thanks to IoT. These applications could make IoT devices more personalized, efficient, and productive by collecting and using data. GANs
Branka Hadji Misheva, Joerg Osterrieder
+8 more sources
Design of e-commerce product price prediction model based on generative adversarial network with adaptive weight adjustment [PDF]
Scientific ReportsE-commerce platforms have amassed extensive transaction data, which serves as a valuable source for price prediction. However, the diversity of commodities poses challenges such as data imbalance, model overfitting, and underfitting.
Abuduaini Abudureheman +2 more
doaj +2 more sources
Triple Generative Adversarial Networks [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 We propose a unified game-theoretical framework to perform classification and conditional image generation given limited supervision. It is formulated as a three-player minimax game consisting of a generator, a classifier and a discriminator, and therefore is referred to as Triple Generative Adversarial Network (Triple-GAN).
Chongxuan Li +4 more
openaire +3 more sources
Super-resolution Reconstruction of MRI Based on DNGAN [PDF]
Jisuanji kexue, 2022 The quality of MRI will affect doctor's judgment on patient's physical conditions,and the high-resolution MRI is more conducive to doctor to make an accurate diagnosis.Using computer technology to perform super-resolution reconstruction of MRI can obtain
DAI Zhao-xia, LI Jin-xin, ZHANG Xiang-dong, XU Xu, MEI Lin, ZHANG Liang
doaj +1 more source
Generative adversarial networks [PDF]
Communications of the ACM, 2020 Generative adversarial networks are a kind of artificial intelligence algorithm designed to solve the generative modeling problem. The goal of a generative model is to study a collection of training examples and learn the probability distribution that generated them.
Goodfellow, Ian J. +7 more
openaire +2 more sources
Quaternion Generative Adversarial Networks [PDF]
, 2022 Accepted as a Chapter for the SPRINGER book "Generative Adversarial Learning: Architectures and Applications"
Grassucci, Eleonora +2 more
openaire +3 more sources
Steganographic generative adversarial networks [PDF]
Twelfth International Conference on Machine Vision (ICMV 2019), 2020 Steganography is collection of methods to hide secret information ("payload") within non-secret information "container"). Its counterpart, Steganalysis, is the practice of determining if a message contains a hidden payload, and recovering it if possible. Presence of hidden payloads is typically detected by a binary classifier.
Volkhonskiy, Denis +2 more
openaire +2 more sources