This is the Linux app named AtomAI whose latest release can be downloaded as 0.8.1sourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named AtomAI with OnWorks for free.
Ikuti petunjuk ini untuk menjalankan aplikasi ini:
- 1. Download aplikasi ini di PC Anda.
- 2. Masuk ke file manager kami https://www.onworks.net/myfiles.php?username=XXXXX dengan username yang anda inginkan.
- 3. Upload aplikasi ini di filemanager tersebut.
- 4. Jalankan emulator online OnWorks Linux atau Windows online atau emulator online MACOS dari situs web ini.
- 5. Dari OS Linux OnWorks yang baru saja Anda mulai, buka file manager kami https://www.onworks.net/myfiles.php?username=XXXXX dengan nama pengguna yang Anda inginkan.
- 6. Download aplikasinya, install dan jalankan.
Tangkapan layar
Ad
AtomAI
DESKRIPSI
AtomAI is a Pytorch-based package for deep and machine-learning analysis of microscopy data that doesn't require any advanced knowledge of Python or machine learning. The intended audience is domain scientists with a basic understanding of how to use NumPy and Matplotlib. It was developed by Maxim Ziatdinov at Oak Ridge National Lab. The purpose of the AtomAI is to provide an environment that bridges the instrument-specific libraries and general physical analysis by enabling the seamless deployment of machine learning algorithms including deep convolutional neural networks, invariant variational autoencoders, and decomposition/unmixing techniques for image and hyperspectral data analysis. Ultimately, it aims to combine the power and flexibility of the PyTorch deep learning framework and the simplicity and intuitive nature of packages such as scikit-learn, with a focus on scientific data.
Fitur
- Exploring causal physical mechanisms via non-Gaussian linear models and deep kernel learning
- Exploring order parameters and dynamic processes in disordered systems via variational autoencoders
- Tracking atomic structure evolution during directed electron beam induced Si-atom motion in graphene via deep machine learning
- Segmentasi semantik
- ImSpec models
- Dokumentasi tersedia
Bahasa Pemrograman
Ular sanca
KATEGORI
This is an application that can also be fetched from https://sourceforge.net/projects/atomai.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
