Search Results for "computer vision vb.net"
Sort By:
Showing 11 open source projects for "computer vision vb.net"
View related business solutions-
Over two-thirds of people reuse passwords across sites, resulting in an increasingly insecure e-commerce ecosystem. Learn how passwordless can not only mitigate these issues but make the authentication experience delightful. Implement Auth0 in any application in just five minutes
-
PhishTitan is a next-generation phishing protection and remediation solution powered by TitanHQ. Our proprietary machine-learning algorithm integrates directly with Microsoft 365, catching and remediating sophisticated phishing attacks Microsoft misses. These sophisticated, zero-day attacks are currently being missed and are where the real damage occurs. Post-delivery remediation (PDR) allows you to remove all phishing emails from your user's inbox, removing risk instantly. Our curated and unique email threat intelligence data is unmatched in visibility, coverage, and accuracy.
-
1
OpenVINO
OpenVINO™ Toolkit repository
OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference. Boost deep learning performance in computer vision, automatic speech recognition, natural language processing and other common tasks. Use models trained with popular frameworks like TensorFlow, PyTorch and more. Reduce resource demands and efficiently deploy on a range of Intel® platforms from edge to cloud. This open-source version includes several components: namely Model Optimizer, OpenVINO™ Runtime, Post-Training... -
2
Datasets
Hub of ready-to-use datasets for ML models
Datasets is a library for easily accessing and sharing datasets, and evaluation metrics for Natural Language Processing (NLP), computer vision, and audio tasks. Load a dataset in a single line of code, and use our powerful data processing methods to quickly get your dataset ready for training in a deep learning model. Backed by the Apache Arrow format, process large datasets with zero-copy reads without any memory constraints for optimal speed and efficiency. We also feature a deep integration... -
3
Colossal-AI
Making large AI models cheaper, faster and more accessible
The Transformer architecture has improved the performance of deep learning models in domains such as Computer Vision and Natural Language Processing. Together with better performance come larger model sizes. This imposes challenges to the memory wall of the current accelerator hardware such as GPU. It is never ideal to train large models such as Vision Transformer, BERT, and GPT on a single GPU or a single machine. There is an urgent demand to train models in a distributed environment. However... -
4
Diffgram
Training data (data labeling, annotation, workflow) for all data types
... the activities of annotation, which produces structured data; ready to be consumed by a machine learning model. Annotation is required because raw media is considered to be unstructured and not usable without it. That’s why training data is required for many modern machine learning use cases including computer vision, natural language processing and speech recognition. -
Institutions throughout the world use CYPHER Learning as their tool of choice to manage all classroom activities. CYPHER Learning is used by organizations ranging from large universities such as STI in the Philippines, school districts such as Santa Barbara Unified School District, to small schools with 20 students in Spain.
-
5
T81 558
Applications of Deep Neural Networks
... structures, Convolution Neural Networks (CNN), Long Short-Term Memory (LSTM), Gated Recurrent Neural Networks (GRU), General Adversarial Networks (GAN) and reinforcement learning. Application of these architectures to computer vision, time series, security, natural language processing (NLP), and data generation will be covered. High-Performance Computing (HPC) aspects will demonstrate how deep learning can be leveraged both on graphical processing units (GPUs), as well as grids. -
6
Machine Learning PyTorch Scikit-Learn
Code Repository for Machine Learning with PyTorch and Scikit-Learn
... this book covers in general, I’d describe it as a comprehensive resource on the fundamental concepts of machine learning and deep learning. The first half of the book introduces readers to machine learning using scikit-learn, the defacto approach for working with tabular datasets. Then, the second half of this book focuses on deep learning, including applications to natural language processing and computer vision. -
7
OpenNN - Open Neural Networks Library
Machine learning algorithms for advanced analytics
OpenNN is a software library written in C++ for advanced analytics. It implements neural networks, the most successful machine learning method. Some typical applications of OpenNN are business intelligence (customer segmentation, churn prevention…), health care (early diagnosis, microarray analysis…) and engineering (performance optimization, predictive maitenance…). OpenNN does not deal with computer vision or natural language processing. The main advantage of OpenNN is its high... -
8
DeepLearning
Deep Learning (Flower Book) mathematical derivation
... feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling and practical methods, and investigates topics such as natural language processing, Applications in speech recognition, computer vision, online recommender systems, bioinformatics, and video games. Finally, the Deep Learning book provides research directions covering theoretical topics including linear factor models, autoencoders, representation learning, structured probabilistic models, etc. -
9
Deep Learning Drizzle
Drench yourself in Deep Learning, Reinforcement Learning
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures! Optimization courses which form the foundation for ML, DL, RL. Computer Vision courses which are DL & ML heavy. Speech recognition courses which are DL heavy. Structured Courses on Geometric, Graph Neural Networks. Section on Autonomous Vehicles. Section on Computer Graphics with ML/DL focus. -
Accept and review any type of submission with Submittable, a cloud-based submission management platform. Whether you're looking to receive editorial, resumes, applications, contest entries, or portfolios, Submittable provides the tools to help you receive and manage all types of digital content so you can make better decsions. Top tools include form customization, team management and reviewing, submitter communication, and reports and data.
-
10
OpenPR stands for Open Pattern Recognition project and is intended to be an open source library for algorithms of image processing, computer vision, natural language processing, pattern recognition, machine learning and the related fields.
-
11
Awesome Recurrent Neural Networks
A curated list of resources dedicated to RNN
... in tensorflow, and much more. Codes, theory, applications, and datasets about natural language processing, robotics, computer vision, and much more.
- Previous
- You're on page 1
- Next