Best AI tools for< Semantic Segmenter >

CVAT is an open-source data annotation platform that helps teams of any size annotate data for machine learning. It is used by companies big and small in a variety of industries, including healthcare, retail, and automotive. CVAT is known for its intuitive user interface, advanced features, and support for a wide range of data formats. It is also highly extensible, allowing users to add their own custom features and integrations.

Datature is an all-in-one platform for building and deploying computer vision models. It provides tools for data management, annotation, training, and deployment, making it easy to develop and implement computer vision solutions. Datature is used by a variety of industries, including healthcare, retail, manufacturing, and agriculture.

Semantic Scholar is a free, AI-powered research tool for scientific literature. It is based at the Allen Institute for AI and provides access to over 217 million papers from all fields of science. Semantic Scholar uses AI to help users discover and explore scientific literature, and to stay up-to-date on the latest research. The tool also includes a number of features to help users manage their research, such as the ability to save papers, create bibliographies, and share research with others.

Biblos Semantic Bible Search & Summary is an AI-powered tool designed to provide a powerful Bible search experience. It offers semantic search capabilities and a powerful understanding model to enhance the user's exploration of the Bible. The tool allows users to search and summarize content from both the Old Testament and the New Testament, providing lightning-fast search results for a seamless user experience.

WhenX is a tool for creating Semantic Alerts that allows users to create robots to monitor the web for specific information. Users can ask questions, and the tool will search the web for answers, monitoring for any changes. It is a personal project not intended for commercial use, and it is open source, built by edmar and hosted on Vercel.

Keytalk AI is a company that specializes in prompt engineering, which is the process of creating prompts that can be used to generate text, images, and other types of content using artificial intelligence (AI) models. Keytalk AI's mission is to make AI more accessible and user-friendly by providing tools and resources that make it easy for people to create and use AI-generated content. The company's flagship product is Keytalk Prompts, a library of pre-written prompts that can be used to generate content on a variety of topics. Keytalk AI also offers a range of other services, including consulting, training, and support.

MaxNotes is an AI voice notes organizer application that helps users efficiently manage and organize their voice notes using artificial intelligence technology. The application allows users to easily record, transcribe, categorize, and search through their voice notes, making it a convenient tool for individuals who rely on voice memos for productivity and organization. With MaxNotes, users can streamline their note-taking process and access important information quickly and effortlessly.

Spin Rewriter AI is an article rewriter that uses artificial intelligence to generate unique, human-quality content. It is the only rewriter that uses the power of Large Language Models (LLMs) to extract the meaning of your articles on an entirely different level. This means that Spin Rewriter AI can pinpoint the meaning of every word in your article and how each word relates to every other word in its context. This allows Spin Rewriter AI to create human-quality readable articles with ZERO machine-generated footprint at a push of a button.

Inedit is an AI-powered editor widget that enhances the ability to edit webpage content instantly. It offers features like AI and inline editing, manual mode for error correction, effortless editing of multiple elements, and the ability to inspect deeper structures of webpages. The tool is powered by OpenAI GPT Models, providing unparalleled flexibility and advanced technology to streamline workflow and enhance productivity.

SmarterFolder is an AI-powered tool designed for MacOS that enables users to perform semantic image searches on their local drive. By utilizing AI technology, users can find photos based on descriptions of the content within the images. The tool ensures full privacy as no images are shared or stored externally, providing a secure and efficient way to organize and retrieve photos.

illumex is a generative semantic fabric platform designed to streamline the process of data and analytics interpretation and rationalization for complex enterprises. It offers augmented analytics creation, suggestive data and analytics utilization monitoring, and automated knowledge documentation to enhance agentic performance for analytics. The platform aims to solve the challenges of traditional tedious data analysis, incongruent data and metrics, and tribal knowledge of data teams.

Maimovie is an AI-powered movie and TV show search engine that helps users find content based on their specific moods or contexts. It offers an infinite number of personal recommendations based on user preferences, as well as live-updated AI curation of movie and TV show rankings trending on popular streaming services. Maimovie provides detailed information about each movie and TV show, including plot, available streaming services, ratings, cast, crew, and similar movies.

Pongo is an AI-powered tool that helps reduce hallucinations in Large Language Models (LLMs) by up to 80%. It utilizes multiple state-of-the-art semantic similarity models and a proprietary ranking algorithm to ensure accurate and relevant search results. Pongo integrates seamlessly with existing pipelines, whether using a vector database or Elasticsearch, and processes top search results to deliver refined and reliable information. Its distributed architecture ensures consistent latency, handling a wide range of requests without compromising speed. Pongo prioritizes data security, operating at runtime with zero data retention and no data leaving its secure AWS VPC.

Level AI is a provider of artificial intelligence (AI)-powered solutions for call centers. Its products include GenAI-automated Quality Assurance, Contact Center and Business Analytics, GenAI-powered VoC Insights, AgentGPT Real-Time Agent Assist, Agent Coaching, Agent Screen Recording, and Artificial Intelligence Integrations. Level AI's solutions are designed to help businesses improve customer experience, increase efficiency, and reduce costs. The company's customers include some of the world's leading customer service organizations, such as Brex and ezCater.

iMessage for Business is a native sales platform that helps convert leads into sales through engaging messaging channels. It offers features like group chats, voice memos, videos, and photos, with flat monthly pricing based on phone lines. The platform is trusted by hundreds of sales teams and aims to provide a more personal and effective way of communication with customers.

Thesify.ai is an AI essay writing tool designed to assist students in academic writing. It offers features such as writing-coach, semantic article search, pre-submission assessment, intelligent paper digest, and agile editor. The tool aims to provide AI-powered assistance, insights, and feedback to help students improve their writing skills while maintaining academic integrity.

Wordmetrics is an AI-powered writing platform that helps content marketers get more traffic. It provides real-time guidance on writing for search, analyzes competing pages, and optimizes content for contextual relevance. Wordmetrics is cloud-based and easy to use, with a simple toolset that lets you log in and go.

Ultra AI is an all-in-one AI command center for products, offering features such as multi-provider AI gateway, prompts manager, semantic caching, logs & analytics, model fallbacks, and rate limiting. It is designed to help users efficiently manage and utilize AI capabilities in their products. The platform is privacy-focused, fast, and provides quick support, making it a valuable tool for businesses looking to leverage AI technology.

Trieve is an AI-first infrastructure API that offers search, recommendations, and RAG capabilities by combining language models with tools for fine-tuning ranking and relevance. It provides features such as semantic vector search, BM25 & SPLADE full-text search, hybrid search, merchandising & relevance tuning, and sub-sentence highlighting. Trieve helps companies build unfair competitive advantages through their search, discovery, and RAG experiences. The platform is built on the best foundations, offering private open-source models, self-hostable options, and easy integration with existing data. With Trieve, users can set up industry-leading search in just 30 minutes and take control of their discovery process.

LangSearch is an AI tool that offers a free Web Search API and Rerank API, serving as the World Engine for AGI. It allows users to connect their LLM applications to access clean, accurate, high-quality context from billions of web documents, including news, images, videos, and more. The tool supports natural language search and provides enhanced search details for various content types.

InternVL scales up the ViT to _**6B parameters**_ and aligns it with LLM. It is a vision-language foundation model that can perform various tasks, including: **Visual Perception** - Linear-Probe Image Classification - Semantic Segmentation - Zero-Shot Image Classification - Multilingual Zero-Shot Image Classification - Zero-Shot Video Classification **Cross-Modal Retrieval** - English Zero-Shot Image-Text Retrieval - Chinese Zero-Shot Image-Text Retrieval - Multilingual Zero-Shot Image-Text Retrieval on XTD **Multimodal Dialogue** - Zero-Shot Image Captioning - Multimodal Benchmarks with Frozen LLM - Multimodal Benchmarks with Trainable LLM - Tiny LVLM InternVL has been shown to achieve state-of-the-art results on a variety of benchmarks. For example, on the MMMU image classification benchmark, InternVL achieves a top-1 accuracy of 51.6%, which is higher than GPT-4V and Gemini Pro. On the DocVQA question answering benchmark, InternVL achieves a score of 82.2%, which is also higher than GPT-4V and Gemini Pro. InternVL is open-sourced and available on Hugging Face. It can be used for a variety of applications, including image classification, object detection, semantic segmentation, image captioning, and question answering.

Awesome Khmer Language is a comprehensive collection of resources for the Khmer language, including tools, datasets, research papers, projects/models, blogs/slides, and miscellaneous items. It covers a wide range of topics related to Khmer language processing, such as character normalization, word segmentation, part-of-speech tagging, optical character recognition, text-to-speech, and more. The repository aims to support the development of natural language processing applications for the Khmer language by providing a diverse set of resources and tools for researchers and developers.

The collection of pre-trained, state-of-the-art AI models. ailia SDK is a self-contained, cross-platform, high-speed inference SDK for AI. The ailia SDK provides a consistent C++ API across Windows, Mac, Linux, iOS, Android, Jetson, and Raspberry Pi platforms. It also supports Unity (C#), Python, Rust, Flutter(Dart) and JNI for efficient AI implementation. The ailia SDK makes extensive use of the GPU through Vulkan and Metal to enable accelerated computing. # Supported models 323 models as of April 8th, 2024

SemanticFinder is a frontend-only live semantic search tool that calculates embeddings and cosine similarity client-side using transformers.js and SOTA embedding models from Huggingface. It allows users to search through large texts like books with pre-indexed examples, customize search parameters, and offers data privacy by keeping input text in the browser. The tool can be used for basic search tasks, analyzing texts for recurring themes, and has potential integrations with various applications like wikis, chat apps, and personal history search. It also provides options for building browser extensions and future ideas for further enhancements and integrations.

Analyze the following text from a github repository (name and readme text at end) . Then, generate a JSON object with the following keys and provide the corresponding information for each key, in lowercase letters: 'description' (detailed description of the repo, must be less than 400 words，Ensure that no line breaks and quotation marks.),'for_jobs' (List 5 jobs suitable for this tool,in lowercase letters), 'ai_keywords' (keywords of the tool,user may use those keyword to find the tool,in lowercase letters), 'for_tasks' (list of 5 specific tasks user can use this tool to do,in lowercase letters), 'answer' (in english languages)

This repository includes papers and blogs about Efficient Transformers, Length Extrapolation, Long Term Memory, Retrieval Augmented Generation(RAG), and Evaluation for Long Context Modeling.

A repository that lists papers related to Large Language Model (LLM) based agents. The repository covers various topics including survey, planning, feedback & reflection, memory mechanism, role playing, game playing, tool usage & human-agent interaction, benchmark & evaluation, environment & platform, agent framework, multi-agent system, and agent fine-tuning. It provides a comprehensive collection of research papers on LLM-based agents, exploring different aspects of AI agent architectures and applications.

Awesome-Efficient-LLM is a curated list focusing on efficient large language models. It includes topics such as knowledge distillation, network pruning, quantization, inference acceleration, efficient MOE, efficient architecture of LLM, KV cache compression, text compression, low-rank decomposition, hardware/system, tuning, and survey. The repository provides a collection of papers and projects related to improving the efficiency of large language models through various techniques like sparsity, quantization, and compression.

AI Audio Datasets List (AI-ADL) is a comprehensive collection of datasets consisting of speech, music, and sound effects, used for Generative AI, AIGC, AI model training, and audio applications. It includes datasets for speech recognition, speech synthesis, music information retrieval, music generation, audio processing, sound synthesis, and more. The repository provides a curated list of diverse datasets suitable for various AI audio tasks.

The Segment Anything Model (SAM) is a powerful tool that allows users to segment any object in an image with just a few clicks. This makes it a great tool for a variety of tasks, such as object detection, tracking, and editing. SAM is also very easy to use, making it a great option for both beginners and experienced users.

Awesome-Segment-Anything is a powerful tool for segmenting and extracting information from various types of data. It provides a user-friendly interface to easily define segmentation rules and apply them to text, images, and other data formats. The tool supports both supervised and unsupervised segmentation methods, allowing users to customize the segmentation process based on their specific needs. With its versatile functionality and intuitive design, Awesome-Segment-Anything is ideal for data analysts, researchers, content creators, and anyone looking to efficiently extract valuable insights from complex datasets.

The AiTLAS toolbox (Artificial Intelligence Toolbox for Earth Observation) includes state-of-the-art machine learning methods for exploratory and predictive analysis of satellite imagery as well as a repository of AI-ready Earth Observation (EO) datasets. It can be easily applied for a variety of Earth Observation tasks, such as land use and cover classification, crop type prediction, localization of specific objects (semantic segmentation), etc. The main goal of AiTLAS is to facilitate better usability and adoption of novel AI methods (and models) by EO experts, while offering easy access and standardized format of EO datasets to AI experts which allows benchmarking of various existing and novel AI methods tailored for EO data.

SimpleAICV_pytorch_training_examples is a repository that provides simple training and testing examples for various computer vision tasks such as image classification, object detection, semantic segmentation, instance segmentation, knowledge distillation, contrastive learning, masked image modeling, OCR text detection, OCR text recognition, human matting, salient object detection, interactive segmentation, image inpainting, and diffusion model tasks. The repository includes support for multiple datasets and networks, along with instructions on how to prepare datasets, train and test models, and use gradio demos. It also offers pretrained models and experiment records for download from huggingface or Baidu-Netdisk. The repository requires specific environments and package installations to run effectively.

Plug-play-modules is a comprehensive collection of plug-and-play modules for AI, deep learning, and computer vision applications. It includes various convolution variants, latest attention mechanisms, feature fusion modules, up-sampling/down-sampling modules, suitable for tasks like image classification, object detection, instance segmentation, semantic segmentation, single object tracking (SOT), multi-object tracking (MOT), infrared object tracking (RGBT), image de-raining, de-fogging, de-blurring, super-resolution, and more. The modules are designed to enhance model performance and feature extraction capabilities across various tasks.

DeepSparkHub is a repository that curates hundreds of application algorithms and models covering various fields in AI and general computing. It supports mainstream intelligent computing scenarios in markets such as smart cities, digital individuals, healthcare, education, communication, energy, and more. The repository provides a wide range of models for tasks such as computer vision, face detection, face recognition, instance segmentation, image generation, knowledge distillation, network pruning, object detection, 3D object detection, OCR, pose estimation, self-supervised learning, semantic segmentation, super resolution, tracking, traffic forecast, GNN, HPC, methodology, multimodal, NLP, recommendation, reinforcement learning, speech recognition, speech synthesis, and 3D reconstruction.

This repository provides advanced AI explainability for PyTorch, offering state-of-the-art methods for Explainable AI in computer vision. It includes a comprehensive collection of Pixel Attribution methods for various tasks like Classification, Object Detection, Semantic Segmentation, and more. The package supports high performance with full batch image support and includes metrics for evaluating and tuning explanations. Users can visualize and interpret model predictions, making it suitable for both production and model development scenarios.

cellseg-models.pytorch is a Python library built upon PyTorch for 2D cell/nuclei instance segmentation models. It provides multi-task encoder-decoder architectures and post-processing methods for segmenting cell/nuclei instances. The library offers high-level API to define segmentation models, open-source datasets for training, flexibility to modify model components, sliding window inference, multi-GPU inference, benchmarking utilities, regularization techniques, and example notebooks for training and finetuning models with different backbones.

MOOSE 2.0 is a leaner, meaner, and stronger tool for 3D medical image segmentation. It is built on the principles of data-centric AI and offers a wide range of segmentation models for both clinical and preclinical settings. MOOSE 2.0 is also versatile, allowing users to use it as a command-line tool for batch processing or as a library package for individual processing in Python projects. With its improved speed, accuracy, and flexibility, MOOSE 2.0 is the go-to tool for segmentation tasks.

Analyse & visualise semantic networks entities and attributes for content creation.

Guiding on Semantic SEO, from understanding core concepts to applying advanced strategies.

BIAN v12.0

Typescript-based expert in NextJS, Semantic-ui

Aids in SPARQL queries for Semantic-Art's Gist Ontology

Talk to Navigation with Large Language Models: Semantic Guesswork as a Heuristic for Planning (LFG)

Helps you build logic security into your GPTs custom instructions. Documentation: https://github.com/infotrix/SSLLMs---Semantic-Secuirty-for-LLM-GPTs

Experto en lógica semántica SEO y resolución de problemas, formado por Pau Segui.

Esperto di SEO in analisi semantica, keyword research e messy middle funnel che interagisce con docs e sheets

Expert in schema.org, guiding precise use of 'additionalType'.

A linguistic explorer that delves into the depths of words and phrases, revealing their richest meanings and most resonant synonyms, closely aligned with their original intent.