This is the Linux app named SimSiam whose latest release can be downloaded as simsiamsourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named SimSiam with OnWorks for free.
برای اجرای این برنامه این دستورالعمل ها را دنبال کنید:
- 1. این برنامه را در رایانه شخصی خود دانلود کنید.
- 2. در فایل منیجر ما https://www.onworks.net/myfiles.php?username=XXXXX نام کاربری مورد نظر خود را وارد کنید.
- 3. این برنامه را در چنین فایل منیجر آپلود کنید.
- 4. OnWorks Linux آنلاین یا شبیه ساز آنلاین ویندوز یا شبیه ساز آنلاین MACOS را از این وب سایت راه اندازی کنید.
- 5. از سیستم عامل لینوکس OnWorks که به تازگی راه اندازی کرده اید، به مدیر فایل ما https://www.onworks.net/myfiles.php?username=XXXXX با نام کاربری که می خواهید بروید.
- 6. اپلیکیشن را دانلود کرده، نصب و اجرا کنید.
عکس ها
Ad
سیم سیام
شرح
SimSiam is a PyTorch implementation of “Exploring Simple Siamese Representation Learning” by Xinlei Chen and Kaiming He. The project introduces a minimalist approach to self-supervised learning that avoids negative pairs, momentum encoders, or large memory banks—key complexities of prior contrastive methods. SimSiam learns image representations by maximizing similarity between two augmented views of the same image through a Siamese neural network with a stop-gradient operation, preventing feature collapse. This elegant yet effective design achieves strong results in unsupervised learning benchmarks such as ImageNet without requiring contrastive losses. The repository provides scripts for both unsupervised pre-training and linear evaluation, using a ResNet-50 backbone by default. It is compatible with multi-GPU distributed training and can be fine-tuned or transferred to downstream tasks like object detection following the same setup as MoCo.
امکانات
- Minimal self-supervised learning framework without negative pairs or momentum encoders
- PyTorch-based implementation optimized for distributed multi-GPU training
- Fully reproducible training pipeline for ImageNet using default hyperparameters from the paper
- Includes both unsupervised pre-training and linear evaluation scripts
- LARS optimizer support via NVIDIA Apex for large-batch training
- Compatible with object detection transfer setups from MoCo
زبان برنامه نویسی
پــایتــون
دسته بندی ها
This is an application that can also be fetched from https://sourceforge.net/projects/simsiam.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.