Search Results for "/storage/emulated/0/android/data/net.sourceforge.uiq3.fx603p/files" - Page 38
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964 projects for "/storage/emulated/0/android/data/net.sourceforge.uiq3.fx603p/files" with 2 filters applied:
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Iris Powered By Generali - Iris puts your customer in control of their identity.Iris Identity Protection API sends identity monitoring and alerts data into your existing digital environment – an ideal solution for businesses that are looking to offer their customers identity protection services without having to build a new product or app from scratch.
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Get full visibility and control over your tasks and projects with Wrike.Wrike offers world-class features that empower cross-functional, distributed, or growing teams take their projects from the initial request stage all the way to tracking work progress and reporting results.
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i3D-converter creates a 3D representation from a couple of images (or a pair of stereo images). This program also performs other Computer Vision operations such as, edge and corner detection, image filtering, getting geometric shapes,...
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NeuroGrid could be thought of as a "Napster for Bookmarks." It allows the user to store data in a web-like fashion, allowing you to associate bookmarks (files/documents/whatever) with multiple keywords. See http://www.neurogrid.net
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...You can write your Envolvable Code with it; You can make your computer write program itself; You can run program without compiling time; You can manage source as data
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Securden Privileged Account ManagerDiscover and manage administrator, service, and web app passwords, keys, and identities. Automate management with approval workflows. Centrally control, audit, monitor, and record all access to critical IT assets.
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Pattern recognition software package. It includes several classification and clustering algorithms. It can read data from a set of images, an ASCII file or a JDBC connection. A small TCP data server with its corresponding JDBC driver is included.
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Anna is a set of AIML files designed to create a chat bot that will win the 2002 Loebner Prize. Anna is a fundamental departure from other bots in that she identifies herself as human and has her personality built up from there.
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UMDS is small, strong and expansible project. The model offers a uniform method of conceptual view of the diverse data as a sequence of bits and a uniform method of keeping and processing this sequence on the external storage.
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If you are looking for a way to get WordNetŽ 's data into your relational DBMS, wordnet2sql is what you need!
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Fungus is a framework for distributed simulation by multi-agents. It uses a very modular architecture. A GUI is provided. In our model, everything is Agent. Even the environnement. You have an access to the communication's 'canals'.
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The full-stack observability platform that protects your dataLayer, tags and conversion dataCode-Cube.io detects issues instantly, alerts you in real time and helps you resolve them fast. No manual QA. No unreliable data. Just data you can trust and act on.
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LFReD. One of the most powerful conversational AI projects and the closest thing to a fully functioning HAL 9000 anywhere. Additional files will be released shortly. Plans to port to C++ and Python in the works.
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Development of a snazzy Java program to simulate the growth and competition of entities in a limited environment.
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C++ library that implements basic data structures and algorithms for computer vision and image processing applications
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The ROSETTA C++ library is a collection of C++ classes and routines that enable discernibility-based empirical modelling and data mining. Comprises useful routines for machine learning in general and for rough set theory in particular.
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pyBoids is a free/open-source project that implements (in Python/TKinter) Craig Reynold's famous boids algorithm. This algorithm intelligently simulates flocking, herding, swarming, and schooling behavior as found in nature.
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The Data Fusion Peer is a multitier computer vision internet application. The system provides image processing, motion tracking, and visualization information. Application will convert data into 3-Deminsional and other digital environments.
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CLIP-ViT-bigG-14-laion2B-39B-b160k
CLIP ViT-bigG/14: Zero-shot image-text model trained on LAION-2B
...Developed by LAION and trained by Mitchell Wortsman on Stability AI’s compute infrastructure, it pairs a ViT-bigG/14 vision transformer with a text encoder to perform contrastive learning on image-text pairs. This model excels at zero-shot image classification, image-to-text and text-to-image retrieval, and can be adapted for tasks such as image captioning or generation guidance. It achieves an impressive 80.1% top-1 accuracy on ImageNet-1k without any fine-tuning, showcasing its robustness in open-domain settings. Its training dataset is uncurated and web-sourced, meaning it reflects the biases and risks of large-scale internet data. ... -
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Interlogy - next generation knowledge storage and prezentation system. Gives wide functionality for knwoledge evaluation. Interlogy is the same as forum, wiki, chat, socialnetwork, but all together.
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OpenVLA 7B
Vision-language-action model for robot control via images and text
...It takes camera images and natural language instructions as input and outputs normalized 7-DoF robot actions, enabling control of multiple robot types across various domains. Built on top of LLaMA-2 and DINOv2/SigLIP visual backbones, it allows both zero-shot inference for known robot setups and parameter-efficient fine-tuning for new domains. The model supports real-world robotics tasks, with robust generalization to environments seen in pretraining. Its actions include delta values for position, orientation, and gripper status, and can be un-normalized based on robot-specific statistics. ... -
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granite-timeseries-ttm-r2
Tiny pre-trained IBM model for multivariate time series forecasting
...Unlike massive foundation models, TTM models are designed to be lightweight yet powerful, with only ~805K parameters, enabling high performance even on CPU or single-GPU machines. The r2 version is pre-trained on ~700M samples (r2.1 expands to ~1B), delivering up to 15% better accuracy than the r1 version. TTM supports both zero-shot and fine-tuned forecasting, handling minutely, hourly, daily, and weekly resolutions. It can integrate exogenous variables, static categorical features, and perform channel-mixing for richer multivariate forecasting. The get_model() utility makes it easy to auto-select the best TTM model for specific context and prediction lengths. ... -
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unidepth-v2-vitl14
Metric monocular depth estimation (vision model)
Estimates absolute (metric) depth from single RGB images, along with camera intrinsics and uncertainty. Designed to generalize across domains (zero-shot) using a self‑prompting camera module and pseudo-spherical prediction space. -
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fashion-clip
CLIP model fine-tuned for zero-shot fashion product classification
FashionCLIP is a domain-adapted CLIP model fine-tuned specifically for the fashion industry, enabling zero-shot classification and retrieval of fashion products. Developed by Patrick John Chia and collaborators, it builds on the CLIP ViT-B/32 architecture and was trained on over 800K image-text pairs from the Farfetch dataset. The model learns to align product images and descriptive text using contrastive learning, enabling it to perform well across various fashion-related tasks without additional supervision. ... -
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VaultGemma
VaultGemma: 1B DP-trained Gemma variant for private NLP tasks
...Training ran on TPU v6e using JAX and Pathways with privacy-preserving algorithms (DP-SGD, truncated Poisson subsampling) and DP scaling laws to balance compute and privacy budgets. Benchmarks on the 1B pre-trained checkpoint show expected utility trade-offs (e.g., HellaSwag 10-shot 39.09, BoolQ 0-shot 62.04, PIQA 0-shot 68.00), reflecting its privacy-first design. -
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A software to implement the existing stereo matching algorithms in computer vision, including the easiest SSD, and the newest algorithms.
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Qwen3-Next
Qwen3-Next: 80B instruct LLM with ultra-long context up to 1M tokens
...The model natively supports a context length of 262K tokens and can be extended up to 1 million tokens using RoPE scaling (YaRN), making it highly capable for processing large documents and extended conversations. Multi-Token Prediction (MTP) boosts both training and inference, while stability optimizations such as weight-decayed and zero-centered layernorm ensure robustness. Benchmarks show it performs comparably to larger models like Qwen3-235B on reasoning, coding, multilingual, and alignment tasks while requiring only a fraction of the training cost. -
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** IMPORTANT NOTICE ** 10 Feb 2006 Code is being moved to the SMI subversion repository (http://smi-protege.stanford.edu/svn/owl/trunk/) Project will continue to be open source. ProtegeOWL info at: http://protege.stanford.edu/overview/protege-owl.html
