Search Results for "image classification using svm java code"
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Showing 7 open source projects for "image classification using svm java code"
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pdf-inspector
Fast Rust library for PDF inspection, classification
pdf-inspector is a fast Rust library for classifying PDFs and extracting structured text without OCR. It distinguishes text-based, scanned, image-based, and mixed documents while returning confidence scores and pages that may need OCR. Its position-aware parser preserves font data, coordinates, reading order, and multi-column layouts. The converter produces clean Markdown with headings, lists, code blocks, links, page breaks, and formatted tables. It supports CID fonts, several encodings,... -
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Tribuo
Tribuo - A Java machine learning library
Tribuo* is a machine learning library written in Java. It provides tools for classification, regression, clustering, model development, and more. It provides a unified interface to many popular third-party ML libraries like xgboost and liblinear. With interfaces to native code, Tribuo also makes it possible to deploy models trained by Python libraries (e.g. scikit-learn, and pytorch) in a Java program. -
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DocWire SDK
Award-winning modern data processing SDK in C++20
DocWire SDK, a standout C++20AI driven data processing tool, has received award from SourceForge and strong backing from Microsoft. It handles nearly 100 file types, empowering efficient text extraction, web data extraction, and document analysis. For businesses, the shift to DocWire SDK signifies a leap forward. It promises comprehensive document format support and the ability to extract valuable insights from email boxes, databases, and websites using cutting-edge AI. DocWire SDK aims to... -
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Google Cloud Vision API examples
Sample code for Google Cloud Vision
The cloud-vision repository is a sample code collection for the Google Cloud Vision API that shows developers how to implement image analysis tasks across a wide range of languages and platforms. It contains examples organized by language and environment, including Go, Java, Node.js, PHP, Python, Ruby, .NET, Android, iOS, and even a Chrome extension, which makes it especially valuable as a cross-platform learning resource. The repository demonstrates concrete image understanding use cases,... -
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WrapImaJ
Multi-platform API for Image Processing systems in Life Sciences
WrapImaJ purposes to be a multi-platform wrapper for different Image Processing systems for: - using the Java programming language. The purpose of WrapImaJ is not to combine an exhaustive collection of all functionalities of different imaging system, but to offer a simple, concise Application Programming Interface (API) - allowing to develop imaging software, the source code of which is independent from the underlying imaging system on which it relies. ... -
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ConvNetJS
Deep learning in Javascript to train convolutional neural networks
ConvNetJS is a Javascript library for training Deep Learning models (Neural Networks) entirely in your browser. Open a tab and you're training. No software requirements, no compilers, no installations, no GPUs, no sweat. ConvNetJS is an implementation of Neural networks, together with nice browser-based demos. It currently supports common Neural Network modules (fully connected layers, non-linearities), classification (SVM/Softmax) and Regression (L2) cost functions, ability to specify and... -
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Aspose for Spring.Java
Aspose for Spring.Java provides Aspose API samples for Spring.Java.
Aspose for Spring.Java provides usage samples / sourcecodes for the demonstration of Aspose API for Java by extending famous Spring Java PetClinic Sample Web Application. This extension of "Spring Java PetClinic Sample Web Application" also shows the Integration of Aspose APIs with Spring MVC, JSP and Maven Project. Latest Release: v1.1
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