Best AI tools for< Computer Engineer >

The Computer Vision Foundation (CVF) is a non-profit organization dedicated to advancing the field of computer vision. CVF organizes several conferences and workshops each year, including the International Conference on Computer Vision (ICCV), the Conference on Computer Vision and Pattern Recognition (CVPR), and the Winter Conference on Applications of Computer Vision (WACV). CVF also publishes the International Journal of Computer Vision (IJCV) and the Computer Vision and Image Understanding (CVIU) journal. The CVF Open Access website provides access to the full text of all CVF-sponsored conference papers. These papers are available for free download in PDF format. The CVF Open Access website also includes links to the arXiv versions of the papers, where available.

OpenCV is a library of programming functions mainly aimed at real-time computer vision. Originally developed by Intel, it was later supported by Willow Garage and is now maintained by Itseez. OpenCV is cross-platform and free for use under the open-source BSD license.

Lexset is an AI tool that provides synthetic data generation services for computer vision model training. It offers a no-code interface to create unlimited data with advanced camera controls and lighting options. Users can simulate AI-scale environments, composite objects into images, and create custom 3D scenarios. Lexset also provides access to GPU nodes, dedicated support, and feature development assistance. The tool aims to improve object detection accuracy and optimize generalization on high-quality synthetic data.

Luxonis is an AI application that offers Visual AI solutions engineered for precision edge inference. The application provides stereo depth cameras with unique features and quality, enabling users to perform advanced vision tasks on-device, reducing latency and bandwidth demands. With open-source DepthAI API, users can create and deploy custom vision solutions that scale with their needs. Luxonis also offers real-world training data for self-improving vision intelligence and operates flawlessly through vibrations, temperature shifts, and extended use. The application integrates advanced sensing capabilities with up to 48MP cameras, wide field of view, IMUs, microphones, ToF, thermal, IR illumination, and active stereo for unparalleled perception.

Viso Suite is a no-code computer vision platform that enables users to build, deploy, and scale computer vision applications. It provides a comprehensive set of tools for data collection, annotation, model training, application development, and deployment. Viso Suite is trusted by leading Fortune Global companies and has been used to develop a wide range of computer vision applications, including object detection, image classification, facial recognition, and anomaly detection.

Roboflow is an AI tool designed for computer vision tasks, offering a platform that allows users to annotate, train, deploy, and perform inference on models. It provides integrations, ecosystem support, and features like notebooks, autodistillation, and supervision. Roboflow caters to various industries such as aerospace, agriculture, healthcare, finance, and more, with a focus on simplifying the development and deployment of computer vision models.

syntheticAIdata is a platform that provides synthetic data for training vision AI models. Synthetic data is generated artificially, and it can be used to augment existing real-world datasets or to create new datasets from scratch. syntheticAIdata's platform is easy to use, and it can be integrated with leading cloud platforms. The company's mission is to make synthetic data accessible to everyone, and to help businesses overcome the challenges of acquiring high-quality data for training their vision AI models.

OpenCV is the world's largest computer vision library. It's open source, contains over 2500 algorithms and is operated by the non-profit Open Source Vision Foundation.

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.

OpenCV.ai is a leading provider of computer vision software and services. The company's team of experts has extensive experience in developing optimized large-scale computer vision solutions. OpenCV.ai's expertise is helping businesses grow in a variety of industries, including medicine, manufacturing, and retail. The company's solutions are used by startups and Fortune 500 companies alike.

PROPHESEE is an AI-driven system developed by Metavision Technologies that leverages Event-Based Vision technology inspired by human vision and neuromorphic engineering. It enables machines to capture hyper-fast and fleeting scene dynamics, manage extreme lighting conditions, and operate with new levels of power efficiency. The system enhances machine intelligence, autonomy, speed, and safety, offering a new era in autonomy, automation, and mobility. PROPHESEE combines patented neuromorphic vision sensors and AI algorithms to create an unparalleled event-based vision system, dynamically driven by live scene events. It significantly improves artificial vision speed and efficiency, reducing energy consumption and computational power requirements.

Clarifai is a full-stack AI developer platform that provides a range of tools and services for building and deploying AI applications. The platform includes a variety of computer vision, natural language processing, and generative AI models, as well as tools for data preparation, model training, and model deployment. Clarifai is used by a variety of businesses and organizations, including Fortune 500 companies, startups, and government agencies.

Synthesis AI is a synthetic data platform that enables more capable and ethical computer vision AI. It provides on-demand labeled images and videos, photorealistic images, and 3D generative AI to help developers build better models faster. Synthesis AI's products include Synthesis Humans, which allows users to create detailed images and videos of digital humans with rich annotations; Synthesis Scenarios, which enables users to craft complex multi-human simulations across a variety of environments; and a range of applications for industries such as ID verification, automotive, avatar creation, virtual fashion, AI fitness, teleconferencing, visual effects, and security.

Big Vision provides consulting services in AI, computer vision, and deep learning. They help businesses build specific AI-driven solutions, create intelligent processes, and establish best practices to reduce human effort and enable faster decision-making. Their enterprise-grade solutions are currently serving millions of requests every month, especially in critical production environments.

Tech Xplore is a leading source of science and technology news, covering the latest breakthroughs in research and innovation across a wide range of disciplines, including artificial intelligence, robotics, computer science, and more. The website provides in-depth articles, interviews with experts, and up-to-date information on the latest developments in the field of AI and its applications.

Amazon Science is a research and development organization within Amazon that focuses on developing new technologies and products in the fields of artificial intelligence, machine learning, and computer science. The organization is home to a team of world-renowned scientists and engineers who are working on a wide range of projects, including developing new algorithms for machine learning, building new computer vision systems, and creating new natural language processing tools. Amazon Science is also responsible for developing new products and services that use these technologies, such as the Amazon Echo and the Amazon Fire TV.

Clarifai is a full-stack AI platform that provides developers and ML engineers with the fastest, production-grade deep learning platform. It offers a wide range of features, including data preparation, model building, model operationalization, and AI workflows. Clarifai is used by a variety of companies, including Fortune 500 companies and startups, to build AI applications in a variety of industries, including retail, manufacturing, and healthcare.

Innovatiana is a data labeling outsourcing company that provides high-quality training data for AI models. They specialize in computer vision, data moderation, document processing, natural language processing, and data collection. Innovatiana is committed to ethical and sustainable practices, and they pay their data labelers fair wages and provide them with good working conditions. They also use a variety of quality control measures to ensure that their data is accurate and reliable.

Gradient Insight is a data science consulting and AI solutions provider. They offer a range of services including generative AI development, machine learning, computer vision, robotics and automation, AI strategy and roadmap, and data analytics. Their team of expert data scientists helps businesses to de-risk their investment in AI and to overcome barriers to engineering innovation. Gradient Insight has worked with clients such as Opitas, a fintech company, and the UK MOD. They offer a smooth and efficient process from consultation to delivery, and ongoing support and improvement.

The Visual Computing & Artificial Intelligence Lab at TUM is a group of research enthusiasts advancing cutting-edge research at the intersection of computer vision, computer graphics, and artificial intelligence. Our research mission is to obtain highly-realistic digital replica of the real world, which include representations of detailed 3D geometries, surface textures, and material definitions of both static and dynamic scene environments. In our research, we heavily build on advances in modern machine learning, and develop novel methods that enable us to learn strong priors to fuel 3D reconstruction techniques. Ultimately, we aim to obtain holographic representations that are visually indistinguishable from the real world, ideally captured from a simple webcam or mobile phone. We believe this is a critical component in facilitating immersive augmented and virtual reality applications, and will have a substantial positive impact in modern digital societies.

The `Call-for-Reviewers` repository aims to collect the latest 'call for reviewers' links from various top CS/ML/AI conferences/journals. It provides an opportunity for individuals in the computer/ machine learning/ artificial intelligence fields to gain review experience for applying for NIW/H1B/EB1 or enhancing their CV. The repository helps users stay updated with the latest research trends and engage with the academic community.

This repository contains the source code for a GEMM & deep learning hardware accelerator system used to validate proposed systolic array hardware architectures implementing efficient matrix multiplication algorithms to increase performance-per-area limits of GEMM & AI accelerators. Achieved results include up to 3× faster CNN inference, >2× higher mults/multiplier/clock cycle, and low area with high clock frequency. The system is specialized for inference of non-sparse DNN models with fixed-point/quantized inputs, fully accelerating all DNN layers in hardware, and highly optimizing GEMM acceleration.

This repository contains course materials for the 'Introduction to Machine Learning' course at Sharif University of Technology. It includes slides, Jupyter notebooks, and exercises for the Fall 2024 semester. The content is continuously updated throughout the semester. Previous semester materials are also accessible. Visit www.SharifML.ir for class videos and additional information.

The 'machine-learning-research' repository is a comprehensive collection of resources related to mathematics, machine learning, deep learning, artificial intelligence, data science, and various scientific fields. It includes materials such as courses, tutorials, books, podcasts, communities, online courses, papers, and dissertations. The repository covers topics ranging from fundamental math skills to advanced machine learning concepts, with a focus on applications in healthcare, genetics, computational biology, precision health, and AI in science. It serves as a valuable resource for individuals interested in learning and researching in the fields of machine learning and related disciplines.

The OpenVINO Build and Deploy repository provides pre-built components and code samples to accelerate the development and deployment of production-grade AI applications across various industries. With the OpenVINO Toolkit from Intel, users can enhance the capabilities of both Intel and non-Intel hardware to meet specific needs. The repository includes AI reference kits, interactive demos, workshops, and step-by-step instructions for building AI applications. Additional resources such as Jupyter notebooks and a Medium blog are also available. The repository is maintained by the AI Evangelist team at Intel, who provide guidance on real-world use cases for the OpenVINO toolkit.

Stable Diffusion is a text-to-image AI model that can generate realistic images from a given text prompt. It is a powerful tool that can be used for a variety of creative and practical applications, such as generating concept art, creating illustrations, and designing products. Stable Diffusion is also a great tool for learning about AI and machine learning. This repository contains a collection of tutorials and resources on how to use Stable Diffusion.

Awesome AI & Data GitHub-Repos is a curated list of essential GitHub repositories covering the AI & ML landscape. It includes resources for Natural Language Processing, Large Language Models, Computer Vision, Data Science, Machine Learning, MLOps, Data Engineering, SQL & Database, and Statistics. The repository aims to provide a comprehensive collection of projects and resources for individuals studying or working in the field of AI and data science.

This repository provides comprehensive roadmaps for various roles in the Data Analytics, Data Science, and Artificial Intelligence industry. It aims to guide individuals, whether students or professionals, in understanding the required skills and timeline for different roles, helping them focus on learning the necessary skills to secure a job. The repository includes detailed guides for roles such as Data Analyst, Data Engineer, Data Scientist, AI Engineer, Computer Vision Engineer, Generative AI Engineer, Machine Learning Engineer, NLP Engineer, and Domain-Specific ML Topics for Researchers.

This repository is a compilation of excellent ML and DL tutorials created by various individuals and organizations. It covers a wide range of topics, including machine learning fundamentals, deep learning, computer vision, natural language processing, reinforcement learning, and more. The resources are organized into categories, making it easy to find the information you need. Whether you're a beginner or an experienced practitioner, you're sure to find something valuable in this repository.

Albumentations is a Python library for image augmentation. Image augmentation is used in deep learning and computer vision tasks to increase the quality of trained models. The purpose of image augmentation is to create new training samples from the existing data.

Kornia is a differentiable computer vision library for PyTorch. It consists of a set of routines and differentiable modules to solve generic computer vision problems. At its core, the package uses PyTorch as its main backend both for efficiency and to take advantage of the reverse-mode auto-differentiation to define and compute the gradient of complex functions.

This repository contains a collection of papers and code for the CVPR 2024 conference. The papers cover a wide range of topics in computer vision, including object detection, image segmentation, image generation, and video analysis. The code provides implementations of the algorithms described in the papers, making it easy for researchers and practitioners to reproduce the results and build upon the work of others. The repository is maintained by a team of researchers at the University of California, Berkeley.

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.

ScreenAgent is a project focused on creating an environment for Visual Language Model agents (VLM Agent) to interact with real computer screens. The project includes designing an automatic control process for agents to interact with the environment and complete multi-step tasks. It also involves building the ScreenAgent dataset, which collects screenshots and action sequences for various daily computer tasks. The project provides a controller client code, configuration files, and model training code to enable users to control a desktop with a large model.

The LandingLens Python library contains the LandingLens development library and examples that show how to integrate your app with LandingLens in a variety of scenarios. The library allows users to acquire images from different sources, run inference on computer vision models deployed in LandingLens, and provides examples in Jupyter Notebooks and Python apps for various tasks such as object detection, home automation, satellite image analysis, license plate detection, and streaming video analysis.

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.

This repository is a rich resource offering examples of synthetic image generation, manipulation, and reasoning using Azure Machine Learning, Computer Vision, OpenAI, and open-source frameworks like Stable Diffusion. It provides practical insights into image processing applications, including content generation, video analysis, avatar creation, and image manipulation with various tools and APIs.

InsPLAD is a dataset and benchmark for power line asset inspection in UAV images. It contains 10,607 high-resolution UAV color images of seventeen unique power line assets with six defects. The dataset is used for object detection, defect classification, and anomaly detection tasks in computer vision. InsPLAD offers challenges like multi-scale objects, intra-class variation, cluttered background, and varied lighting conditions, aiming to improve state-of-the-art methods in the field.

The 'awesome-mobile-robotics' repository is a curated list of important content related to Mobile Robotics and AI. It includes resources such as courses, books, datasets, software and libraries, podcasts, conferences, journals, companies and jobs, laboratories and research groups, and miscellaneous resources. The repository covers a wide range of topics in the field of Mobile Robotics and AI, providing valuable information for enthusiasts, researchers, and professionals in the domain.

AirSLAM is an efficient visual SLAM system designed to tackle short-term and long-term illumination challenges. It combines deep learning techniques with traditional optimization methods, featuring a unified CNN for keypoint and structural line extraction. The system includes a relocalization pipeline for map reuse, accelerated using C++ and NVIDIA TensorRT. Outperforming other SLAM systems in challenging environments, it runs at 73Hz on PC and 40Hz on embedded platforms.

Expert in computer systems, focusing on hardware and components.

Guides in buying computers and explaining features

Expert on Computer Organization and Architecture

Mind Map & Flowchart Assistant for Quantum Computer Design

Expert in computer vision, deep learning, ready to assist you with 3d and geometric computer vision. https://github.com/kornia/pixie

Professional guide in computer vision, offering clear, insightful advice.

Your expert in SLAM and computer vision.

AI Recruiter for AI Engineering roles

AI Hardware Engineer

Autonomous Driving Dev Assistant

Generates PyTorch code from neural network images.

Der digitale Assistent zum KI-Bootcamp

Plateforme innovante en IA pour passionnés de technologie, offrant conseils et articles via 100 IA collaboratives.

A tech-focused AI expert explaining AI generation, tools, and best practices.

Concise NeRF guide, summarizing top papers and aiding research.

Friendly and professional guide for street sign app development.

AI for GPU, CPU, memory, and storage recommendation

Personal AI mentor for deep learning education

Leading AI & Media Expert: In-depth, Ethical, Insightful, developed on OpenAI

Your little team of AI experts.