Search Results for "processing"

...Instead of relying purely on traditional embedding-based retrieval or RAG systems, Memobase uses profile and timeline structures to deliver memory that reflects user context efficiently and meaningfully. The system focuses on three principal performance metrics: high search performance, reduced large language model (LLM) costs through batch processing techniques, and low latency with minimal SQL operations. Memobase supports integration with existing LLM workflows via APIs and SDKs (including Python, Node, and Go), making it easy to adopt within diverse application stacks.

VGGSfM is an advanced structure-from-motion (SfM) framework jointly developed by Meta AI Research (GenAI) and the University of Oxford’s Visual Geometry Group (VGG). It reconstructs 3D geometry, dense depth, and camera poses directly from unordered or sequential images and videos. The system combines learned feature matching and geometric optimization to generate high-quality camera calibrations, sparse/dense point clouds, and depth maps in standard COLMAP format. Version 2.0 adds support...

...AI File Sorter helps tidy up cluttered folders such as Downloads, external drives, or NAS storage by grouping files based on filenames, extensions, folder context, and learned organization patterns. The application can run fully offline using local AI models such as Mistral 7B or LLaMa 3B. When using local models, all processing happens entirely on your device — no files, images, or metadata are uploaded, and no telemetry is sent.

This project extends the Proximus development environment to support deployment of AI workloads on next-generation AMD Ryzen™ AI processors, such as the Ryzen™ AI 7 PRO 7840U featured in the Lenovo ThinkPad T14s Gen 4 ,one of the first true AI PCs with an onboard Neural Processing Unit (NPU) capable of 16 TOPS (trillion operations per second). Originally designed for use with Windows 11 Pro, this runtime was further enhanced to work under Linux environments, allowing developers and researchers to fully utilize the AMD AI Engine across both platforms. This cross-platform support is a major innovation, enabling AI workload portability, integration into CI environments, and deployment into Linux-based research and production pipelines.

...It extends the Fast R-CNN framework by introducing multiple network “paths” to enhance feature extraction and object recognition robustness. The MultiPath architecture incorporates skip connections and multi-scale processing to capture both fine-grained details and high-level context within a single detection pipeline. This results in improved detection accuracy across various object sizes and categories compared to standard single-path architectures. The repository supports training, evaluation, and visualization for object detection tasks on popular datasets such as PASCAL VOC and MS COCO. ...

MARF is a general cross-platform framework with a collection of algorithms for audio (voice, speech, and sound) and natural language text analysis and recognition along with sample applications (identification, NLP, etc.) of its use, implemented in Java.

A test suite and benchmark for exact Euclidean distance transform algorithms used in Image Processing and computational geometry. It evaluates the exactness and speed of algorithms for a large number of test cases. Results can be visualized in Scilab.

NOTE: I couldn't keep up this project to align with latest Unicode spec. Not sure I may be continuing. You can try Myanmar3 from Myanmar NLP or WinUniInnwa or https://sourceforge.net/projects/prahita/ or something better compliant font. ~Victor --- [This is UniBurma - UniMM project workshop area. This project currently have two productions, UniBurma and UniMM. For more descriptive info about this project, please visit http://unimm.org/. You can browse lastest source from SVN trunk.]

The Infomap NLP software performs automatic indexing of words and documents from free-text corpora, using a variant of LSA to enable information retrieval and other applications. It was developed by the Infomap Project at Stanford University's CSLI.

The book index generator generate the back-of-book index for Thai book automatically.