Pytorch Dc TtsText to Speech with PyTorch (English and Mongolian)
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Easycnneasy convolution neural network
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DrlnDensely Residual Laplacian Super-resolution, IEEE Pattern Analysis and Machine Intelligence (TPAMI), 2020
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Awesome Deep NeuroevolutionA collection of Deep Neuroevolution resources or evolutionary algorithms applying in Deep Learning (constantly updating)
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Ti PoolingTI-pooling: transformation-invariant pooling for feature learning in Convolutional Neural Networks
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Machine learning lecturesCollection of lectures and lab lectures on machine learning and deep learning. Lab practices in Python and TensorFlow.
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DeepwayThis project is an aid to the blind. Till date there has been no technological advancement in the way the blind navigate. So I have used deep learning particularly convolutional neural networks so that they can navigate through the streets.
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CompactcnncascadeA binary library for very fast face detection using compact CNNs.
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Ml Fraud DetectionCredit card fraud detection through logistic regression, k-means, and deep learning.
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Kiu Net PytorchOfficial Pytorch Code of KiU-Net for Image Segmentation - MICCAI 2020 (Oral)
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TenginekitTengineKit - Free, Fast, Easy, Real-Time Face Detection & Face Landmarks & Face Attributes & Hand Detection & Hand Landmarks & Body Detection & Body Landmarks & Iris Landmarks & Yolov5 SDK On Mobile.
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VenomAll Terrain Autonomous Quadruped
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Deeppose tfDeepPose implementation on TensorFlow. Original Paper http://arxiv.org/abs/1312.4659
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All Conv KerasAll Convolutional Network: (https://arxiv.org/abs/1412.6806#) implementation in Keras
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KvaeKalman Variational Auto-Encoder
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ParticlesSequential Monte Carlo in python
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PythonmlArtificial neural network classes and tools in Python and TensorFlow.
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AlphatradingAn workflow in factor-based equity trading, including factor analysis and factor modeling. For well-established factor models, I implement APT model, BARRA's risk model and dynamic multi-factor model in this project.
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Chainer Cifar10Various CNN models for CIFAR10 with Chainer
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DeepcpgDeep neural networks for predicting CpG methylation
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Aw nasaw_nas: A Modularized and Extensible NAS Framework
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ImagenetPytorch Imagenet Models Example + Transfer Learning (and fine-tuning)
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Sigver wiwdLearned representation for Offline Handwritten Signature Verification. Models and code to extract features from signature images.
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Awesome Robotic ToolingTooling for professional robotic development in C++ and Python with a touch of ROS, autonomous driving and aerospace.
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PixorPyTorch Implementation of PIXOR
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Intelegent locklock mechanism with face recognition and liveness detection
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Shiftresnet CifarResNet with Shift, Depthwise, or Convolutional Operations for CIFAR-100, CIFAR-10 on PyTorch
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GpndGenerative Probabilistic Novelty Detection with Adversarial Autoencoders
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Rul NetDeep learning approach for estimation of Remaining Useful Life (RUL) of an engine
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Self Driving VehicleSimulation of self-driving vehicles in Unity. This is also an implementation of the Hybrid A* pathfinding algorithm which is useful if you are interested in pathfinding for vehicles.
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Cs231n Convolutional Neural Networks SolutionsAssignment solutions for the CS231n course taught by Stanford on visual recognition. Spring 2017 solutions are for both deep learning frameworks: TensorFlow and PyTorch.
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AlgobookA beginner-friendly project to help you in open-source contributions. Data Structures & Algorithms in various programming languages Please leave a star ⭐ to support this project! ✨
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Cyclegan KerasKeras implementation of CycleGAN using a tensorflow backend.
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OpentrajHuman Trajectory Prediction Dataset Benchmark (ACCV 2020)
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Deep architectA general, modular, and programmable architecture search framework
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AognetCode for CVPR 2019 paper: " Learning Deep Compositional Grammatical Architectures for Visual Recognition"
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DensepointDensePoint: Learning Densely Contextual Representation for Efficient Point Cloud Processing (ICCV 2019)
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Visualizingcnn 🙈A PyTorch implementation of the paper "Visualizing and Understanding Convolutional Networks." (ECCV 2014)
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Facedet实现常用基于深度学习的人脸检测算法
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Attribute Aware Attention[ACM MM 2018] Attribute-Aware Attention Model for Fine-grained Representation Learning
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