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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.
⚡ Automatically decrypt encryptions without knowing the key or cipher, decode encodings, and crack hashes ⚡
A WebGL accelerated JavaScript library for training and deploying ML models.
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
(⌐■_■) - Deep Reinforcement Learning instrumenting bettercap for WiFi pwning.
DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.
BigDL: Distributed TensorFlow, Keras and PyTorch on Apache Spark/Flink & Ray
Attempt at tracking states of the arts and recent results (bibliography) on speech recognition.
Text Classification Algorithms: A Survey
A deep neural network that learns to drive in video games
A deep neural network that directly reconstructs the motion of a 3D human skeleton from monocular video [ToG 2020]
Deep and conventional community detection related papers, implementations, datasets, and tools.
An easy to use C# deep learning library with CUDA/OpenCL support
Powerful computer vision assisted Lego mosaic creator · Over 1 million images created (so far!)
A Pytorch implementation of "Splitter: Learning Node Representations that Capture Multiple Social Contexts" (WWW 2019).
WB color augmenter improves the accuracy of image classification and image semantic segmentation methods by emulating different WB effects (ICCV 2019) [Python & Matlab].
Convolutional Neural Network for German Traffic Sign Recognition Benchmark
Open Toolkit for Painless Object Detection
Reinforcement learning (RL) implementation of imperfect information game Mahjong using markov decision processes to predict future game states
Two-stream CNN for gender classification and biometric identification using a dataset of 11K hand images.
[EXPERIMENTAL] Facebook-like automatic alternative (alt) text for images using object detection with pre-trained model.