Search Results for "handwriting recognition source code"

¿Airtest provides cross-platform APIs, including app installation, simulated input, assertion and so forth. Airtest uses image recognition technology to locate UI elements so that you can automate games and apps without injecting any code. Airtest cases can be easily run on large device farms, using the command line or python API. HTML reports with detailed info and screen recording allow you to quickly locate failure points. NetEase builds Airlab on top of the Airtest Project. AirtestIDE is...

Jittor is a high-performance deep learning framework based on JIT compiling and meta-operators. The whole framework and meta-operators are compiled just in time. A powerful op compiler and tuner are integrated into Jittor. It allowed us to generate high-performance code specialized for your model. Jittor also contains a wealth of high-performance model libraries, including image recognition, detection, segmentation, generation, differentiable rendering, geometric learning, reinforcement...

Cerberus Content Management System is a dynamic, secure and infinitely expandable CMS designed after a Unix-Like model. It is a custom written Web Application Framework ( W.A.F. ) with a consistent and custom written Pre-Hyper-Text-Post-Processor Programming Code Framework ( P.C.F. ). This Web Application Software Project' aim is to be the fastest and most secure Web Application Framework, Web Application Programming Code Framework, Text, Voice and Video Communications Platform and Content...

Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR) and by community contributors. Yangqing Jia created the project during his PhD at UC Berkeley. Caffe is released under the BSD 2-Clause license. Expressive architecture encourages application and innovation. Models and optimization are defined by configuration without hard-coding. Switch between CPU and GPU by setting a single flag to train on a GPU machine...

The Accord.NET Framework provides machine learning, mathematics, statistics, computer vision, computer audition, and several scientific computing related methods and techniques to .NET. The project is compatible with the .NET Framework. NET Standard, .NET Core, and Mono.

Framework for making Windows applications that are one .exe file in AutoHotKey_L,C++,C#, VB.NET,Java,Groovy,Common Lisp,Nemerle,Ruby,Python,PHP,Lua,Tcl,Perl,Jint,S#,WSH VBScript,HTML/JavaScript/CSS,COM, PowerShell without compiling . For .NET 4.

Neuroph OCR - Handwriting Recognition is developed to recognize hand written letter and characters. It's engine derived's from the Java Neural Network Framework - Neuroph and as such it can be used as a standalone project or a Neuroph plug in.