{"id":62166,"date":"2025-04-08T15:47:57","date_gmt":"2025-04-08T15:47:57","guid":{"rendered":""},"modified":"2025-04-08T15:47:57","modified_gmt":"2025-04-08T15:47:57","slug":"%d8%aa%d8%b1%d8%ac%d9%85%d9%87-%d9%81%d8%a7%d8%b1%d8%b3%db%8c-%d9%85%d9%82%d8%a7%d9%84%d9%87-62166","status":"publish","type":"product","link":"https:\/\/express24.ir\/d\/product\/%d8%aa%d8%b1%d8%ac%d9%85%d9%87-%d9%81%d8%a7%d8%b1%d8%b3%db%8c-%d9%85%d9%82%d8%a7%d9%84%d9%87-62166\/","title":{"rendered":"\u062a\u0631\u062c\u0645\u0647 \u0641\u0627\u0631\u0633\u06cc \u0645\u0642\u0627\u0644\u0647 FQGA-stingle: \u0628\u0647 \u0633\u0645\u062a \u062f\u0648\u0631\u0647 \u0647\u0627\u06cc \u0622\u0645\u0648\u0632\u0634 \u06a9\u0645\u062a\u0631\u06cc \u0648 \u067e\u0627\u0631\u0627\u0645\u062a\u0631\u0647\u0627\u06cc \u0645\u062f\u0644 \u06a9\u0645\u062a\u0631 \u0628\u0631\u0627\u06cc \u06a9\u0627\u0631\u0647\u0627\u06cc \u062a\u0631\u062c\u0645\u0647 \u062a\u0635\u0648\u06cc\u0631 \u0628\u0647 \u062a\u0635\u0648\u06cc\u0631"},"content":{"rendered":"\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\u0639\u0646\u0648\u0627\u0646 \u0645\u0642\u0627\u0644\u0647 \u0628\u0647 \u0627\u0646\u06af\u0644\u06cc\u0633\u06cc <\/td>\nFQGA-single: Towards Fewer Training Epochs and Fewer Model Parameters for Image-to-Image Translation Tasks<\/td>\n<\/tr>\n
\u0639\u0646\u0648\u0627\u0646 \u0645\u0642\u0627\u0644\u0647 \u0628\u0647 \u0641\u0627\u0631\u0633\u06cc <\/td>\n\u062a\u0631\u062c\u0645\u0647 \u0641\u0627\u0631\u0633\u06cc \u0645\u0642\u0627\u0644\u0647 FQGA-stingle: \u0628\u0647 \u0633\u0645\u062a \u062f\u0648\u0631\u0647 \u0647\u0627\u06cc \u0622\u0645\u0648\u0632\u0634 \u06a9\u0645\u062a\u0631\u06cc \u0648 \u067e\u0627\u0631\u0627\u0645\u062a\u0631\u0647\u0627\u06cc \u0645\u062f\u0644 \u06a9\u0645\u062a\u0631 \u0628\u0631\u0627\u06cc \u06a9\u0627\u0631\u0647\u0627\u06cc \u062a\u0631\u062c\u0645\u0647 \u062a\u0635\u0648\u06cc\u0631 \u0628\u0647 \u062a\u0635\u0648\u06cc\u0631<\/td>\n<\/tr>\n
\u0646\u0648\u06cc\u0633\u0646\u062f\u06af\u0627\u0646 <\/td>\nCho Yang<\/td>\n<\/tr>\n
\u0641\u0631\u0645\u062a \u0645\u0642\u0627\u0644\u0647 \u0627\u0646\u06af\u0644\u06cc\u0633\u06cc <\/td>\nPDF<\/td>\n<\/tr>\n
\u0632\u0628\u0627\u0646 \u0645\u0642\u0627\u0644\u0647 \u062a\u062d\u0648\u06cc\u0644\u06cc <\/td>\n\u062a\u0631\u062c\u0645\u0647 \u0641\u0627\u0631\u0633\u06cc<\/td>\n<\/tr>\n
\u0641\u0631\u0645\u062a \u0645\u0642\u0627\u0644\u0647 \u062a\u0631\u062c\u0645\u0647 \u0634\u062f\u0647 <\/td>\n\u0628\u0647 \u0635\u0648\u0631\u062a \u0641\u0627\u06cc\u0644 \u0648\u0631\u062f<\/td>\n<\/tr>\n
\u0646\u062d\u0648\u0647 \u062a\u062d\u0648\u06cc\u0644 \u062a\u0631\u062c\u0645\u0647 <\/td>\n\u062f\u0648 \u062a\u0627 \u0633\u0647 \u0631\u0648\u0632 \u067e\u0633 \u0627\u0632 \u062b\u0628\u062a \u0633\u0641\u0627\u0631\u0634 (\u0628\u0647 \u0635\u0648\u0631\u062a \u0641\u0627\u06cc\u0644 \u062f\u0627\u0646\u0644\u0648\u062f\u06cc)<\/td>\n<\/tr>\n
\u062a\u0639\u062f\u0627\u062f \u0635\u0641\u062d\u0627\u062a<\/td>\n15<\/td>\n<\/tr>\n
\u0644\u06cc\u0646\u06a9 \u062f\u0627\u0646\u0644\u0648\u062f \u0631\u0627\u06cc\u06af\u0627\u0646 \u0645\u0642\u0627\u0644\u0647 \u0627\u0646\u06af\u0644\u06cc\u0633\u06cc<\/td>\n\u062f\u0627\u0646\u0644\u0648\u062f \u0645\u0642\u0627\u0644\u0647<\/a><\/td>\n<\/tr>\n
\u062f\u0633\u062a\u0647 \u0628\u0646\u062f\u06cc \u0645\u0648\u0636\u0648\u0639\u0627\u062a <\/td>\nImage and Video Processing,Computer Vision and Pattern Recognition,Machine Learning,\u067e\u0631\u062f\u0627\u0632\u0634 \u062a\u0635\u0648\u06cc\u0631 \u0648 \u0641\u06cc\u0644\u0645 , \u062f\u06cc\u062f \u0631\u0627\u06cc\u0627\u0646\u0647 \u0648 \u062a\u0634\u062e\u06cc\u0635 \u0627\u0644\u06af\u0648\u06cc , \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646 ,<\/td>\n<\/tr>\n
\u062a\u0648\u0636\u06cc\u062d\u0627\u062a <\/td>\nSubmitted 22 August, 2024; v1 submitted 17 August, 2024; originally announced August 2024.<\/td>\n<\/tr>\n
\u062a\u0648\u0636\u06cc\u062d\u0627\u062a \u0628\u0647 \u0641\u0627\u0631\u0633\u06cc <\/td>\n\u0627\u0631\u0633\u0627\u0644 \u0634\u062f\u0647 \u062f\u0631 22 \u0627\u0648\u062a 2024 \u061bV1 \u0627\u0631\u0633\u0627\u0644 \u0634\u062f\u0647 17 \u0627\u0648\u062a 2024 \u061b\u062f\u0631 \u0627\u0628\u062a\u062f\u0627 \u0627\u0648\u062a 2024 \u0627\u0639\u0644\u0627\u0645 \u0634\u062f.<\/td>\n<\/tr>\n
\u0627\u0637\u0644\u0627\u0639\u0627\u062a \u0628\u06cc\u0634\u062a\u0631 \u0627\u0632 \u0627\u06cc\u0646 \u0645\u0642\u0627\u0644\u0647 \u062f\u0631 \u067e\u0627\u06cc\u06af\u0627\u0647 \u0647\u0627\u06cc \u0639\u0644\u0645\u06cc <\/td>\n\n INSPIRE HEP<\/a>
\n
\n NASA ADS<\/a>
\n
\n Google Scholar<\/a>
\n
\n Semantic Scholar<\/a>
\n
\n arXiv<\/a><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\r\n\r\n \r\n \r\n \r\n \r\n
\u0641\u0631\u0645\u062a \u0627\u0631\u0627\u0626\u0647 \u062a\u0631\u062c\u0645\u0647 \u0645\u0642\u0627\u0644\u0647 <\/td>\r\n \u062a\u062d\u0648\u06cc\u0644 \u0628\u0647 \u0635\u0648\u0631\u062a \u0641\u0627\u06cc\u0644 \u0648\u0631\u062f<\/td>\r\n <\/tr>\r\n
\u0632\u0645\u0627\u0646 \u062a\u062d\u0648\u06cc\u0644 \u062a\u0631\u062c\u0645\u0647 \u0645\u0642\u0627\u0644\u0647 <\/td>\r\n \u0628\u06cc\u0646 2 \u062a\u0627 3 \u0631\u0648\u0632 \u067e\u0633 \u0627\u0632 \u062b\u0628\u062a \u0633\u0641\u0627\u0631\u0634<\/td>\r\n <\/tr>\r\n\t
\u06a9\u06cc\u0641\u06cc\u062a \u062a\u0631\u062c\u0645\u0647 <\/td>\r\n \u0628\u0633\u06cc\u0627\u0631 \u0628\u0627\u0644\u0627. \u0645\u0642\u0627\u0644\u0647 \u0641\u0642\u0637 \u062a\u0648\u0633\u0637 \u0645\u062a\u0631\u062c\u0645\u06cc\u0646 \u0628\u0627 \u0645\u062f\u0631\u06a9 \u062f\u0627\u0646\u0634\u06af\u0627\u0647\u06cc \u0645\u062a\u0631\u062c\u0645\u06cc \u062a\u0631\u062c\u0645\u0647 \u0645\u06cc\u200c\u0634\u0648\u062f.<\/td>\r\n <\/tr>\r\n\t\t
\u062c\u062f\u0627\u0648\u0644 \u0648 \u0641\u0631\u0645\u0648\u0644 \u0647\u0627 <\/td>\r\n \u06a9\u0644\u06cc\u0647 \u062c\u062f\u0627\u0648\u0644 \u0648 \u0641\u0631\u0645\u0648\u0644 \u0647\u0627 \u0646\u06cc\u0632 \u062f\u0631 \u0641\u0627\u06cc\u0644 \u062a\u062d\u0648\u06cc\u0644\u06cc \u0648\u0631\u062f \u062f\u0631\u062c \u0645\u06cc\u200c\u0634\u0648\u0646\u062f.<\/td>\r\n <\/tr>\r\n<\/table>\r\n\r\n\n

\u0686\u06a9\u06cc\u062f\u0647<\/h2>\n

CycleGAN was trained on SynthRAD Grand Challenge Dataset using the single-epoch modification (SEM) method proposed in this paper which is referred to as (CycleGAN-single) compared to the usual method of training CycleGAN on around 200 epochs (CycleGAN-multi). Model performance were evaluated qualitatively and quantitatively with quantitative performance metrics like PSNR, SSIM, MAE and MSE. The consideration of both quantitative and qualitative performance when evaluating a model is unique to certain image-to-image translation tasks like medical imaging of patient data as detailed in this paper. Also, this paper shows that good quantitative performance does not always imply good qualitative performance and the converse is also not always True (i.e. good qualitative performance does not always imply good quantitative performance). This paper also proposes a lightweight model called FQGA (Fast Paired Image-to-Image Translation Quarter-Generator Adversary) which has 1\/4 the number of parameters compared to CycleGAN (when comparing their Generator Models). FQGA outperforms CycleGAN qualitatively and quantitatively even only after training on 20 epochs. Finally, using SEM method on FQGA allowed it to again outperform CycleGAN both quantitatively and qualitatively. These performance gains even with fewer model parameters and fewer epochs (which will result in time and computational savings) may also be applicable to other image-to-image translation tasks in Machine Learning apart from the Medical image-translation task discussed in this paper between Cone Beam Computed Tomography (CBCT) and Computed Tomography (CT) images.<\/p>\n

\u0686\u06a9\u06cc\u062f\u0647 \u0628\u0647 \u0641\u0627\u0631\u0633\u06cc (\u062a\u0631\u062c\u0645\u0647 \u0645\u0627\u0634\u06cc\u0646\u06cc)<\/h2>\n

Cyclegan \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0631\u0648\u0634 \u0627\u0635\u0644\u0627\u062d \u062a\u06a9 epoch (SEM) \u062f\u0631 \u0627\u06cc\u0646 \u0645\u0642\u0627\u0644\u0647 \u06a9\u0647 \u062f\u0631 \u0627\u06cc\u0646 \u0645\u0642\u0627\u0644\u0647 \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 (CycleGan-Single) \u062f\u0631 \u0645\u0642\u0627\u06cc\u0633\u0647 \u0628\u0627 \u0631\u0648\u0634 \u0645\u0639\u0645\u0648\u0644 CycleGan \u062f\u0631 \u062d\u062f\u0648\u062f 200 \u062f\u0648\u0631\u0647 (Cyclegan-Multi) \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 (Cyclegan-Single) \u06af\u0641\u062a\u0647 \u0645\u06cc \u0634\u0648\u062f \u060c \u062f\u0631 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc Synthrad Grand Challenge \u0622\u0645\u0648\u0632\u0634 \u062f\u0627\u062f\u0647 \u0634\u062f.\u0639\u0645\u0644\u06a9\u0631\u062f \u0645\u062f\u0644 \u0627\u0632 \u0646\u0638\u0631 \u06a9\u06cc\u0641\u06cc \u0648 \u06a9\u0645\u06cc \u0628\u0627 \u0645\u0639\u06cc\u0627\u0631\u0647\u0627\u06cc \u0639\u0645\u0644\u06a9\u0631\u062f \u06a9\u0645\u06cc \u0645\u0627\u0646\u0646\u062f PSNR \u060c SSIM \u060c MAE \u0648 MSE \u0645\u0648\u0631\u062f \u0628\u0631\u0631\u0633\u06cc \u0642\u0631\u0627\u0631 \u06af\u0631\u0641\u062a.\u062f\u0631 \u0646\u0638\u0631 \u06af\u0631\u0641\u062a\u0646 \u0647\u0631 \u062f\u0648 \u0639\u0645\u0644\u06a9\u0631\u062f \u06a9\u0645\u06cc \u0648 \u06a9\u06cc\u0641\u06cc \u0647\u0646\u06af\u0627\u0645 \u0627\u0631\u0632\u06cc\u0627\u0628\u06cc \u06cc\u06a9 \u0645\u062f\u0644 \u060c \u0628\u0631\u0627\u06cc \u0628\u0631\u062e\u06cc \u0627\u0632 \u0648\u0638\u0627\u06cc\u0641 \u062a\u0631\u062c\u0645\u0647 \u062a\u0635\u0648\u06cc\u0631 \u0628\u0647 \u062a\u0635\u0648\u06cc\u0631 \u0645\u0627\u0646\u0646\u062f \u062a\u0635\u0648\u06cc\u0631\u0628\u0631\u062f\u0627\u0631\u06cc \u067e\u0632\u0634\u06a9\u06cc \u0627\u0632 \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc \u0628\u06cc\u0645\u0627\u0631 \u0628\u0647 \u0637\u0648\u0631 \u0645\u0641\u0635\u0644 \u062f\u0631 \u0627\u06cc\u0646 \u0645\u0642\u0627\u0644\u0647 \u0645\u0646\u062d\u0635\u0631 \u0628\u0647 \u0641\u0631\u062f \u0627\u0633\u062a.\u0647\u0645\u0686\u0646\u06cc\u0646 \u060c \u0627\u06cc\u0646 \u0645\u0642\u0627\u0644\u0647 \u0646\u0634\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f \u06a9\u0647 \u0639\u0645\u0644\u06a9\u0631\u062f \u06a9\u0645\u06cc \u062e\u0648\u0628 \u0647\u0645\u06cc\u0634\u0647 \u0628\u0647 \u0645\u0639\u0646\u0627\u06cc \u0639\u0645\u0644\u06a9\u0631\u062f \u06a9\u06cc\u0641\u06cc \u062e\u0648\u0628 \u0646\u06cc\u0633\u062a \u0648 \u0645\u06a9\u0627\u0644\u0645\u0647 \u0646\u06cc\u0632 \u0647\u0645\u06cc\u0634\u0647 \u062f\u0631\u0633\u062a \u0646\u06cc\u0633\u062a (\u06cc\u0639\u0646\u06cc \u0639\u0645\u0644\u06a9\u0631\u062f \u06a9\u06cc\u0641\u06cc \u062e\u0648\u0628 \u0647\u0645\u06cc\u0634\u0647 \u0628\u0647 \u0645\u0639\u0646\u0627\u06cc 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Cyclegan \u0627\u0632 \u0644\u062d\u0627\u0638 \u06a9\u06cc\u0641\u06cc \u0648 \u06a9\u0645\u06cc \u0628\u0647\u062a\u0631 \u0627\u0633\u062a \u062d\u062a\u06cc \u067e\u0633 \u0627\u0632 \u0622\u0645\u0648\u0632\u0634 \u062f\u0631 20 \u062f\u0648\u0631\u0647.\u0633\u0631\u0627\u0646\u062c\u0627\u0645 \u060c \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0631\u0648\u0634 SEM \u062f\u0631 FQGA \u0628\u0647 \u0622\u0646 \u0627\u062c\u0627\u0632\u0647 \u062f\u0627\u062f \u062a\u0627 \u062f\u0648\u0628\u0627\u0631\u0647 \u0627\u0632 CycleGan \u0647\u0645 \u0627\u0632 \u0646\u0638\u0631 \u06a9\u0645\u06cc \u0648 \u0647\u0645 \u0627\u0632 \u0646\u0638\u0631 \u06a9\u06cc\u0641\u06cc \u0628\u0647\u062a\u0631 \u0639\u0645\u0644 \u06a9\u0646\u062f.\u0627\u06cc\u0646 \u0639\u0645\u0644\u06a9\u0631\u062f \u062d\u062a\u06cc \u0628\u0627 \u067e\u0627\u0631\u0627\u0645\u062a\u0631\u0647\u0627\u06cc \u0645\u062f\u0644 \u06a9\u0645\u062a\u0631 \u0648 \u062f\u0648\u0631\u0647 \u0647\u0627\u06cc \u06a9\u0645\u062a\u0631\u06cc (\u06a9\u0647 \u0645\u0646\u062c\u0631 \u0628\u0647 \u0635\u0631\u0641\u0647 \u062c\u0648\u06cc\u06cc \u062f\u0631 \u0632\u0645\u0627\u0646 \u0648 \u0645\u062d\u0627\u0633\u0628\u0627\u062a\u06cc \u0645\u06cc \u0634\u0648\u062f) \u0646\u06cc\u0632 \u0645\u0645\u06a9\u0646 \u0627\u0633\u062a \u0628\u0631\u0627\u06cc \u0633\u0627\u06cc\u0631 \u06a9\u0627\u0631\u0647\u0627\u06cc \u062a\u0631\u062c\u0645\u0647 \u062a\u0635\u0648\u06cc\u0631 \u0628\u0647 \u062a\u0635\u0648\u06cc\u0631 \u062f\u0631 \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646 \u062c\u062f\u0627 \u0627\u0632 \u06a9\u0627\u0631 \u062a\u0631\u062c\u0645\u0647 \u062a\u0635\u0648\u06cc\u0631 \u067e\u0632\u0634\u06a9\u06cc \u06a9\u0647 \u062f\u0631 \u0627\u06cc\u0646 \u0645\u0642\u0627\u0644\u0647 \u0645\u0648\u0631\u062f \u0628\u062d\u062b \u0642\u0631\u0627\u0631 \u06af\u0631\u0641\u062a\u0647 \u0627\u0633\u062a \u060c \u06a9\u0627\u0631\u0628\u0631\u062f \u062f\u0627\u0634\u062a\u0647 \u0628\u0627\u0634\u062f.\u062a\u0648\u0645\u0648\u06af\u0631\u0627\u0641\u06cc \u0645\u062d\u0627\u0633\u0628\u0647 \u0634\u062f\u0647 \u067e\u0631\u062a\u0648 Cone (CBCT) \u0648 \u062a\u0648\u0645\u0648\u06af\u0631\u0627\u0641\u06cc \u06a9\u0627\u0645\u067e\u06cc\u0648\u062a\u0631\u06cc (CT).<\/p>\n\r\n\r\n \r\n \r\n \r\n \r\n
\u0641\u0631\u0645\u062a \u0627\u0631\u0627\u0626\u0647 \u062a\u0631\u062c\u0645\u0647 \u0645\u0642\u0627\u0644\u0647 <\/td>\r\n \u062a\u062d\u0648\u06cc\u0644 \u0628\u0647 \u0635\u0648\u0631\u062a \u0641\u0627\u06cc\u0644 \u0648\u0631\u062f<\/td>\r\n <\/tr>\r\n
\u0632\u0645\u0627\u0646 \u062a\u062d\u0648\u06cc\u0644 \u062a\u0631\u062c\u0645\u0647 \u0645\u0642\u0627\u0644\u0647 <\/td>\r\n \u0628\u06cc\u0646 2 \u062a\u0627 3 \u0631\u0648\u0632 \u067e\u0633 \u0627\u0632 \u062b\u0628\u062a \u0633\u0641\u0627\u0631\u0634<\/td>\r\n <\/tr>\r\n\t
\u06a9\u06cc\u0641\u06cc\u062a \u062a\u0631\u062c\u0645\u0647 <\/td>\r\n \u0628\u0633\u06cc\u0627\u0631 \u0628\u0627\u0644\u0627. \u0645\u0642\u0627\u0644\u0647 \u0641\u0642\u0637 \u062a\u0648\u0633\u0637 \u0645\u062a\u0631\u062c\u0645\u06cc\u0646 \u0628\u0627 \u0645\u062f\u0631\u06a9 \u062f\u0627\u0646\u0634\u06af\u0627\u0647\u06cc \u0645\u062a\u0631\u062c\u0645\u06cc \u062a\u0631\u062c\u0645\u0647 \u0645\u06cc\u200c\u0634\u0648\u062f.<\/td>\r\n <\/tr>\r\n\t\t
\u062c\u062f\u0627\u0648\u0644 \u0648 \u0641\u0631\u0645\u0648\u0644 \u0647\u0627 <\/td>\r\n \u06a9\u0644\u06cc\u0647 \u062c\u062f\u0627\u0648\u0644 \u0648 \u0641\u0631\u0645\u0648\u0644 \u0647\u0627 \u0646\u06cc\u0632 \u062f\u0631 \u0641\u0627\u06cc\u0644 \u062a\u062d\u0648\u06cc\u0644\u06cc \u0648\u0631\u062f \u062f\u0631\u062c \u0645\u06cc\u200c\u0634\u0648\u0646\u062f.<\/td>\r\n <\/tr>\r\n<\/table>\r\n\r\n\n","protected":false},"excerpt":{"rendered":"

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