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深度神经网络
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Deep neural networks (DNNs) are a class of artificial neural networks (ANNs) that are deep in the sense that they have many layers of hidden units between the input and output layers. Deep neural networks are a type of deep learning, which is a type of machine learning. Deep neural networks are used in a variety of applications, including speech recognition, computer vision, and natural language processing. Deep neural networks are used in a variety of applications, including speech recognition, computer vision, and natural language processing.
An Open Source Machine Learning Framework for Everyone
Deepfakes Software For All
Learn OpenCV : C++ and Python Examples
YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet )
Open standard for machine learning interoperability
DeepFaceLab is the leading software for creating deepfakes.
Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit
machine learning and deep learning tutorials, articles and other resources
Offline speech recognition API for Android, iOS, Raspberry Pi and servers with Python, Java, C# and Node
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch.
pix2code: Generating Code from a Graphical User Interface Screenshot
A paper list of object detection using deep learning.
Turn your two-bit doodles into fine artworks with deep neural networks, generate seamless textures from photos, transfer style from one image to another, perform example-based upscaling, but wait... there's more! (An implementation of Semantic Style Transfer.)
Techniques for deep learning with satellite & aerial imagery
OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient.
🦙 LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022
WebGL-accelerated ML // linear algebra // automatic differentiation for JavaScript.