0% Complete
صفحه اصلی
/
بیست و نهمین کنفرانس مهندسی برق ایران
Multi wasserstien distance
نویسندگان :
Atefeh Ziaei Moghadam
1
Hamed Azarnoush
2
Seyyed Ali Seyyedsalehi
3
1- دانشگاه امیرکبیر
2- دانشگاه امیرکبیر
3- دانشگاه امیرکبیر
کلمات کلیدی :
conditional generative adversarial network image-to-image translation, stain transfer, pathology
چکیده :
Conditional GANs (CGANs) use a condition to generate images. Adding a class condition to the discriminator helps improve the training process of GANs and has been widely used for CGAN. Therefore, many loss functions have been proposed for the discriminator to add class conditions to it. Many of them have the problem of adjusting weights. This paper presents a simple yet new loss function that uses class labels, but no adjusting is required. This loss function is based on WGAN-GP loss, and the discriminator has outputs of the same order (the reason for no adjusting). More specifically, the discriminator has K (the number of classes) outputs, and each of them is used to compute the distance between fake and real samples of one class. Another loss to enable the discriminator to classify is also proposed by applying softmax to the outputs and adding cross-entropy to our first loss. The proposed losses function is applied to a CGAN for image-to-image translation (here stain transformation for pathological images). The performances of proposed losses with some state-of-the-art losses are compared using Histogram Intersection Score between generated images using different loss functions and a reference image. The accuracy of a classifier is also computed to measure the quality of generated images. Our first loss performs almost similar to the loss that achieved the best results
لیست مقالات
لیست مقالات بایگانی شده
یک روش موازی برای تخمین حالت سریع در سیستم های قدرت با ابعاد بزرگ با استفاده از تکنیک جداسازی گراف
بهنام کریم سرمدی - احمد صالحی دوبخشری
Design and Demonstration of a Novel Microfluidic Channel for Trapping Circulating Tumor Cells with Magnetophoresis
Atin Bakhshi - Seyed Ehsan Hosseininasab - Vahid Ghafouri - Mehdi Rahmanian - Majid Badiei Rostami
Lane Change Decision Making Using Deep Reinforcement Learning
Pedram Lamei - Mohammad Haeri
The most descriptive surprise definition for brain’s EEG response to visual and auditory oddball tasks
Mohammad Mahdi Kiani - Zahra Mousavi - Hamid Aghajan
مدلسازی محدودیت های عملی سیستم های ترکیبی انرژی الکتریکی- حرارتی با استفاده از تبدیلات پیشرفته برنامهریزی ریاضی
ریحانه حسن آبادی - حسین شریف زاده
Extension Network of Radiomics-based Deeply Supervised U-Net (ERDU) For Prostate Image Segmentation
Mahdi Ashtarian - Karim Faez - Marjan Firouznia - Hamidreza Amindavar
طراحی کنترل کننده مقاوم برای مدل غیرخطی بیماری کووید-19
آرمان مرزبان - الهام امینی بروجنی
Anomaly Detection in Urban Water Distribution Grids Using Fog Computing Architecture
Sara Mirzaie - Mohammadreza Avazaghaei - Omid Bushehrian
Design of a Full Swing 20-Transistors Full Adder Cell based on CNTFET with High Speed and Low PDP
Amir Baghi Rahin - Afshin Kadivarian - Vahid Baghi Rahin
Distributed Deep Reinforcement Learning for Radio Resource Management in O-RAN
Ahmad Ahmadi Siahpoush - Vahid Shah-Mansouri
بیشتر
ثمین همایش، سامانه مدیریت کنفرانس ها و جشنواره ها - نگارش 42.0.4