Best AI tools for< Duplicate Receipt >

Quetext is a plagiarism checker and AI content detector that helps students, teachers, and professionals identify potential plagiarism and AI in their work. With its deep search technology, contextual analysis, and smart algorithms, Quetext makes checking writing easier and more accurate. Quetext also offers a variety of features such as bulk uploads, source exclusion, enhanced citation generator, grammar & spell check, and Deep Search. With its rich and intuitive feedback, Quetext helps users find plagiarism and AI with less stress.

Nero Platinum Suite is a comprehensive software collection for Windows PCs that provides a wide range of multimedia capabilities, including burning, managing, optimizing, and editing photos, videos, and music files. It includes various AI-powered features such as the Nero AI Image Upscaler, Nero AI Video Upscaler, and Nero AI Photo Tagger, which enhance and simplify multimedia tasks.

Goodlookup is a smart function for spreadsheet users that gets very close to semantic understanding. It’s a pre-trained model that has the intuition of GPT-3 and the join capabilities of fuzzy matching. Use it like vlookup or index match to speed up your topic clustering work in google sheets!

Duplikate is a next-generation AI-powered Community Management tool designed to assist users in managing their social media accounts more efficiently. It helps users save time by retrieving relevant social media posts, categorizing them, and duplicating them with modifications to better suit their audience. The tool is powered by OpenAI and offers features such as post scraping, filtering, and copying, with upcoming features including image generation. Users have praised Duplikate for its ability to streamline content creation, improve engagement, and save time in managing social media accounts.

Blobr is an AI tool designed to optimize Google Ads spending by providing AI agents that can reduce costs from 10% to 20%. The tool allows users to stay in control and validate changes while offering features such as Negative and Duplicate Keywords Finder, Ad Copy Optimizer, CPC Bid Optimizer, Location, Device & Timing Bid Optimizer, and Keyword Ideas Finder. Blobr helps users maximize every advertising dollar by automating keyword identification, optimizing bids, and improving ad quality scores. It saves time by freeing up teams from repetitive tasks and allows for continuous experimentation with control. Trusted by industry leaders, Blobr's AI agents work in real-time to provide recommendations and insights for better campaign performance.

Trust Stamp is a global provider of AI-powered identity services offering a full suite of identity tools, including biometric multi-factor authentication, document validation, identity validation, duplicate detection, and geolocation services. The application is designed to empower organizations across various sectors with advanced biometric identity solutions to reduce fraud, protect personal data privacy, increase operational efficiency, and reach a broader user base worldwide through unique data transformation and comparison capabilities. Founded in 2016, Trust Stamp has achieved significant milestones in net sales, gross profit, and strategic partnerships, positioning itself as a leader in the identity verification industry.

AppZen is an AI-powered application designed for modern finance teams to streamline accounts payable processes, automate invoice and expense auditing, and improve compliance. It offers features such as Autonomous AP for invoice automation, Expense Audit for T&E spend management, and Card Audit for analyzing card spend. AppZen's AI learns and understands business practices, ensures compliance, and integrates with existing systems easily. The application helps prevent duplicate spend, fraud, and FCPA violations, making it a valuable tool for finance professionals.

Dart is an AI project management software designed to empower teams to work smarter, streamline tasks, and achieve more with less effort. It offers features like task execution, subtask generation, project planning, duplicate detection, roadmaps, calendar views, document management, integrations with workplace tools, and more. Dart is used by teams across various roles in organizations to drive focus, innovation, and impact. The tool's AI capabilities automate routine tasks, enhance project reporting, and provide actionable insights for better decision-making.

Snapy is an AI-powered video editing and generation tool that helps content creators create short videos, edit podcasts, and remove silent parts from videos. It offers a range of features such as turning text prompts into short videos, condensing long videos into engaging short clips, automatically removing silent parts from audio files, and auto-trimming, removing duplicate sentences and filler words, and adding subtitles to short videos. Snapy is designed to save time and effort for content creators, allowing them to publish more content, create more engaging videos, and improve the quality of their audio and video content.

ONERECOVERY is a professional data recovery solution for Windows that offers comprehensive and expert solutions to recover lost data from various storage devices. The software is designed to handle data loss for over 1,000 scenarios, including accidental deletion, formatting errors, virus attacks, and more. ONERECOVERY provides features such as file recovery for Windows and Mac, file duplicate finder, photo and video recovery, hard drive recovery, SD card data recovery, and more. With a user-friendly interface, quick and efficient scanning, and compatibility with diverse operating systems and storage devices, ONERECOVERY is a reliable and secure data recovery tool trusted by millions of users worldwide.

DVC is an open-source platform for managing machine learning data and experiments. It provides a unified interface for working with data from various sources, including local files, cloud storage, and databases. DVC also includes tools for versioning data and experiments, tracking metrics, and automating compute resources. DVC is designed to make it easy for data scientists and machine learning engineers to collaborate on projects and share their work with others.

Lenso.ai is an AI-powered reverse image search tool that allows users to explore billions of images from the web with advanced AI technology. It offers a more accurate and efficient process of reverse image search compared to traditional methods. Users can search for places, people, duplicates, and related images effortlessly. The tool is designed to cater to diverse needs, from professional photographers to marketers and enthusiasts, providing a faster, easier, and more accurate image search experience.

The AI photo organizer is a user-friendly web application that utilizes neural networks to help users securely and efficiently organize their photo collections. Users can create custom classes, sort photos, eliminate duplicates, and manage their data locally on their own computer. The application provides a seamless photo management experience, emphasizing simplicity and privacy.

Hints is a sales AI assistant that helps sales reps to get more hours in a day while keeping CRM data accurate automatically. It works with Salesforce, Hubspot, and Pipedrive. With Hints, sales reps can log and retrieve CRM data on any device with chat and voice, get guidance on their next steps, and reminders of what's missing. Hints can also help sales reps to create complex CRM updates in seconds, find duplicates, suggest actions, automatically create associations, and look up sales data through chat and voice commands. Hints can assist sales reps in building the perfect sales process for their team and provides fast onboarding for new sales reps.

Bricks is an AI-first spreadsheet application that simplifies the process of creating and sharing reports, presentations, charts, and visuals using your data. It eliminates the need for advanced spreadsheet expertise, allowing users to effortlessly generate various types of content. Bricks offers a wide range of pre-built templates and tools to enhance productivity and creativity in data analysis and visualization.

Restb.ai is a leading provider of visual insights for real estate companies, utilizing computer vision and AI to analyze property images. The application offers solutions for AVMs, iBuyers, investors, appraisals, inspections, property search, marketing, insurance companies, and more. By providing actionable and unique data at scale, Restb.ai helps improve valuation accuracy, automate manual processes, and enhance property interactions. The platform enables users to leverage visual insights to optimize valuations, automate report quality checks, enhance listings, improve data collection, and more.

The website offers content moderation and image analysis products using powerful APIs to automatically assess, filter, and moderate images, videos, and text. It provides features such as image moderation, video moderation, text moderation, AI image detection, and video anonymization. The application helps in detecting unwanted content, AI-generated images, and personal information in videos. It also offers tools to identify near-duplicates, spam, and abusive links, and prevent phishing and circumvention attempts. The platform is fast, scalable, accurate, easy to integrate, and privacy compliant, making it suitable for various industries like marketplaces, dating apps, and news platforms.

Anea is a unique marketplace for custom-made jewelry, where users can turn their dreams into reality with the help of AI technology. The platform connects customers with Danish goldsmiths to handcraft their personalized jewelry pieces. Anea offers a wide range of jewelry options, from delicate and stackable sets to statement pieces and wedding collections. With a focus on sustainability and ethical sourcing, Anea ensures a secure shopping experience for its users.

LearnOpenCV is a repository containing code for Computer Vision, Deep learning, and AI research articles shared on the blog LearnOpenCV.com. It serves as a resource for individuals looking to enhance their expertise in AI through various courses offered by OpenCV. The repository includes a wide range of topics such as image inpainting, instance segmentation, robotics, deep learning models, and more, providing practical implementations and code examples for readers to explore and learn from.

MachinaScript For Robots is a dynamic set of tools and a LLM-JSON-based language designed to empower humans in the creation of their own robots. It facilitates the animation of generative movements, the integration of personality, and the teaching of new skills with a high degree of autonomy. With MachinaScript, users can control a wide range of electronic components, including Arduinos, Raspberry Pis, servo motors, cameras, sensors, and more. The tool enables the creation of intelligent robots accessible to everyone, allowing for complex tasks to be performed with elegance and precision.

unsight.dev is a tool built on Nuxt that helps detect duplicate GitHub issues and areas of concern across related repositories. It utilizes Nitro server API routes, GitHub API, and a GitHub App, along with UnoCSS. The tool is deployed on Cloudflare with NuxtHub, using Workers AI, Workers KV, and Vectorize. It also offers a browser extension soon to be released. Users can try the app locally for tweaking the UI and setting up a full development environment as a GitHub App.

Trieve is an advanced relevance API for hybrid search, recommendations, and RAG. It offers a range of features including self-hosting, semantic dense vector search, typo tolerant full-text/neural search, sub-sentence highlighting, recommendations, convenient RAG API routes, the ability to bring your own models, hybrid search with cross-encoder re-ranking, recency biasing, tunable popularity-based ranking, filtering, duplicate detection, and grouping. Trieve is designed to be flexible and customizable, allowing users to tailor it to their specific needs. It is also easy to use, with a simple API and well-documented features.

The LLM-Aided OCR Project is an advanced system that enhances Optical Character Recognition (OCR) output by leveraging natural language processing techniques and large language models. It offers features like PDF to image conversion, OCR using Tesseract, error correction using LLMs, smart text chunking, markdown formatting, duplicate content removal, quality assessment, support for local and cloud-based LLMs, asynchronous processing, detailed logging, and GPU acceleration. The project provides detailed technical overview, text processing pipeline, LLM integration, token management, quality assessment, logging, configuration, and customization. It requires Python 3.12+, Tesseract OCR engine, PDF2Image library, PyTesseract, and optional OpenAI or Anthropic API support for cloud-based LLMs. The installation process involves setting up the project, installing dependencies, and configuring environment variables. Users can place a PDF file in the project directory, update input file path, and run the script to generate post-processed text. The project optimizes processing with concurrent processing, context preservation, and adaptive token management. Configuration settings include choosing between local or API-based LLMs, selecting API provider, specifying models, and setting context size for local LLMs. Output files include raw OCR output and LLM-corrected text. Limitations include performance dependency on LLM quality and time-consuming processing for large documents.

**deep** doctection is a Python library that orchestrates document extraction and document layout analysis tasks using deep learning models. It does not implement models but enables you to build pipelines using highly acknowledged libraries for object detection, OCR and selected NLP tasks and provides an integrated framework for fine-tuning, evaluating and running models. For more specific text processing tasks use one of the many other great NLP libraries. **deep** doctection focuses on applications and is made for those who want to solve real world problems related to document extraction from PDFs or scans in various image formats. **deep** doctection provides model wrappers of supported libraries for various tasks to be integrated into pipelines. Its core function does not depend on any specific deep learning library. Selected models for the following tasks are currently supported: * Document layout analysis including table recognition in Tensorflow with **Tensorpack**, or PyTorch with **Detectron2**, * OCR with support of **Tesseract**, **DocTr** (Tensorflow and PyTorch implementations available) and a wrapper to an API for a commercial solution, * Text mining for native PDFs with **pdfplumber**, * Language detection with **fastText**, * Deskewing and rotating images with **jdeskew**. * Document and token classification with all LayoutLM models provided by the **Transformer library**. (Yes, you can use any LayoutLM-model with any of the provided OCR-or pdfplumber tools straight away!). * Table detection and table structure recognition with **table-transformer**. * There is a small dataset for token classification available and a lot of new tutorials to show, how to train and evaluate this dataset using LayoutLMv1, LayoutLMv2, LayoutXLM and LayoutLMv3. * Comprehensive configuration of **analyzer** like choosing different models, output parsing, OCR selection. Check this notebook or the docs for more infos. * Document layout analysis and table recognition now runs with **Torchscript** (CPU) as well and **Detectron2** is not required anymore for basic inference. * [**new**] More angle predictors for determining the rotation of a document based on **Tesseract** and **DocTr** (not contained in the built-in Analyzer). * [**new**] Token classification with **LiLT** via **transformers**. We have added a model wrapper for token classification with LiLT and added a some LiLT models to the model catalog that seem to look promising, especially if you want to train a model on non-english data. The training script for LayoutLM can be used for LiLT as well and we will be providing a notebook on how to train a model on a custom dataset soon. **deep** doctection provides on top of that methods for pre-processing inputs to models like cropping or resizing and to post-process results, like validating duplicate outputs, relating words to detected layout segments or ordering words into contiguous text. You will get an output in JSON format that you can customize even further by yourself. Have a look at the **introduction notebook** in the notebook repo for an easy start. Check the **release notes** for recent updates. **deep** doctection or its support libraries provide pre-trained models that are in most of the cases available at the **Hugging Face Model Hub** or that will be automatically downloaded once requested. For instance, you can find pre-trained object detection models from the Tensorpack or Detectron2 framework for coarse layout analysis, table cell detection and table recognition. Training is a substantial part to get pipelines ready on some specific domain, let it be document layout analysis, document classification or NER. **deep** doctection provides training scripts for models that are based on trainers developed from the library that hosts the model code. Moreover, **deep** doctection hosts code to some well established datasets like **Publaynet** that makes it easy to experiment. It also contains mappings from widely used data formats like COCO and it has a dataset framework (akin to **datasets** so that setting up training on a custom dataset becomes very easy. **This notebook** shows you how to do this. **deep** doctection comes equipped with a framework that allows you to evaluate predictions of a single or multiple models in a pipeline against some ground truth. Check again **here** how it is done. Having set up a pipeline it takes you a few lines of code to instantiate the pipeline and after a for loop all pages will be processed through the pipeline.

Swirl is an open-source software that allows users to simultaneously search multiple content sources and receive AI-ranked results. It connects to various data sources, including databases, public data services, and enterprise sources, and utilizes AI and LLMs to generate insights and answers based on the user's data. Swirl is easy to use, requiring only the download of a YML file, starting in Docker, and searching with Swirl. Users can add credentials to preloaded SearchProviders to access more sources. Swirl also offers integration with ChatGPT as a configured AI model. It adapts and distributes user queries to anything with a search API, re-ranking the unified results using Large Language Models without extracting or indexing anything. Swirl includes five Google Programmable Search Engines (PSEs) to get users up and running quickly. Key features of Swirl include Microsoft 365 integration, SearchProvider configurations, query adaptation, synchronous or asynchronous search federation, optional subscribe feature, pipelining of Processor stages, results stored in SQLite3 or PostgreSQL, built-in Query Transformation support, matching on word stems and handling of stopwords, duplicate detection, re-ranking of unified results using Cosine Vector Similarity, result mixers, page through all results requested, sample data sets, optional spell correction, optional search/result expiration service, easily extensible Connector and Mixer objects, and a welcoming community for collaboration and support.

This repository contains the training and inference code needed to replicate the winning solution to the AI Mathematical Olympiad - Progress Prize 1. It consists of fine-tuning DeepSeekMath-Base 7B, high-quality training datasets, a self-consistency decoding algorithm, and carefully chosen validation sets. The training methodology involves Chain of Thought (CoT) and Tool Integrated Reasoning (TIR) training stages. Two datasets, NuminaMath-CoT and NuminaMath-TIR, were used to fine-tune the models. The models were trained using open-source libraries like TRL, PyTorch, vLLM, and DeepSpeed. Post-training quantization to 8-bit precision was done to improve performance on Kaggle's T4 GPUs. The project structure includes scripts for training, quantization, and inference, along with necessary installation instructions and hardware/software specifications.

Janus is a series of unified multimodal understanding and generation models, including Janus-Pro, Janus, and JanusFlow. Janus-Pro is an advanced version that improves both multimodal understanding and visual generation significantly. Janus decouples visual encoding for unified multimodal understanding and generation, surpassing previous models. JanusFlow harmonizes autoregression and rectified flow for unified multimodal understanding and generation, achieving comparable or superior performance to specialized models. The models are available for download and usage, supporting a broad range of research in academic and commercial communities.

This repo hosts tutorial documentation for running generative AI models on NVIDIA Jetson devices. The documentation is auto-generated and hosted on GitHub Pages using their CI/CD feature to automatically generate/update the HTML documentation site upon new commits.

The AI Comic Factory is a tool that allows you to create your own AI comics with a single prompt. It uses a large language model (LLM) to generate the story and dialogue, and a rendering API to generate the panel images. The AI Comic Factory is open-source and can be run on your own website or computer. It is a great tool for anyone who wants to create their own comics, or for anyone who is interested in the potential of AI for storytelling.

AIOStreams is a versatile tool that combines streams from various addons into one platform, offering extensive customization options. Users can change result formats, filter results by various criteria, remove duplicates, prioritize services, sort results, specify size limits, and more. The tool scrapes results from selected addons, applies user configurations, and presents the results in a unified manner. It simplifies the process of finding and accessing desired content from multiple sources, enhancing user experience and efficiency.

SynthLang is a tool designed to optimize AI prompts by reducing costs and improving processing speed. It brings academic rigor to prompt engineering, creating precise and powerful AI interactions. The tool includes core components like a Translator Engine, Performance Optimization, Testing Framework, and Technical Architecture. It offers mathematical precision, academic rigor, enhanced security, a modern interface, and instant testing. Users can integrate mathematical frameworks, model complex relationships, and apply structured prompts to various domains. Security features include API key management and data privacy. The tool also provides a CLI for prompt engineering and optimization capabilities.

AIL framework is a modular framework to analyze potential information leaks from unstructured data sources like pastes from Pastebin or similar services or unstructured data streams. AIL framework is flexible and can be extended to support other functionalities to mine or process sensitive information (e.g. data leak prevention).

SuperDuperDB is a Python framework for integrating AI models, APIs, and vector search engines directly with your existing databases, including hosting of your own models, streaming inference and scalable model training/fine-tuning. Build, deploy and manage any AI application without the need for complex pipelines, infrastructure as well as specialized vector databases, and moving our data there, by integrating AI at your data's source: - Generative AI, LLMs, RAG, vector search - Standard machine learning use-cases (classification, segmentation, regression, forecasting recommendation etc.) - Custom AI use-cases involving specialized models - Even the most complex applications/workflows in which different models work together SuperDuperDB is **not** a database. Think `db = superduper(db)`: SuperDuperDB transforms your databases into an intelligent platform that allows you to leverage the full AI and Python ecosystem. A single development and deployment environment for all your AI applications in one place, fully scalable and easy to manage.

AIL framework is a modular framework to analyze potential information leaks from unstructured data sources like pastes from Pastebin or similar services or unstructured data streams. AIL framework is flexible and can be extended to support other functionalities to mine or process sensitive information (e.g. data leak prevention).

OptScale is an open-source FinOps and MLOps platform that provides cloud cost optimization for all types of organizations and MLOps capabilities like experiment tracking, model versioning, ML leaderboards.

I guide users on obtaining receipts from Web services.

Provide the information about each receipt from your shopping.

Create, analyze & duplicate customized automated message campaigns to boost retention & drive revenue for your website or app

Maintain the originality of your work with our Plagiarism Checker. This plagiarism checker identifies duplicate content, ensuring your work's uniqueness and integrity.

Type “Start” and Get Exact Details on Image Generation and/or Duplication

完美复制输入的文字

Confirms image uploads without analysis or detail.

Checks blogs for Google plugin plagiarism.

Active, formal analyst of potential name duplicates.

Fix mismatched entries in your data

Specializes in organizing business card data into various formats