Python Deep Learning

Deep Sort with PyTorch Update(1-1-2020) Changes fix bugs refactor code accerate detection by adding nms on gpu Latest Update(07-22) Changes bug fix (Thanks @JieChen91 and @yingsen1 for bug r

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PyTracking A general python framework for visual object tracking and video object segmentation, based on PyTorch. New version released! Code for our CVPR 2020 paper Probabilistic Regression for Visual Tracking. T

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Joint Detection and Embedding for fast multi-object tracking

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tslearn The machine learning toolkit for time series analysis in Python Section Description Installation Installing the dependencies and tslearn

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Welcome to Spektral Spektral is a Python library for graph deep learning, based on the Keras API and TensorFlow 2. The main goal of this project is to provide a simple but flexible framework for creating graph neural networks (

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Aim — a super-easy way to record, search and compare AI experiments

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Welcome to Spektral Spektral is a Python library for graph deep learning, based on the Keras API and TensorFlow 2. The main goal of this project is to provide a simple but flexible framework for creating graph neural networks (

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TensorFlow Tutorial - used by Nvidia Learn TensorFlow from scratch by examples and visualizations with interactive jupyter notebooks. Learn to compete in the Kaggle leaf detection challenge! All exercises are designed to be run

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PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....

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Collection of papers, datasets, code and other resources for object detection and tracking using deep learning Papers Static Detection Region Proposal RCNN YOLO SSD RetinaNet Anchor Free

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Unsupervised single image depth prediction with CNNs

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Use supervised learning to illuminate the latent space of GAN for controlled generation and edit

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Implementation on EfficientNet model. Keras.

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Afshine Amidi
VIP cheatsheets for Stanford's CS 221 Artificial Intelligence

afshinea/stanford-cs-221-artificial-intelligence

VIP cheatsheets for Stanford's CS 221 Artificial Intelligence

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Feature Selector: Simple Feature Selection in Python Feature selector is a tool for dimensionality reduction of machine learning datasets. Methods There are five methods used to identify features to remove: Missin

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Status: Maintenance (expect bug fixes and minor updates) mujoco-py MuJoCo is a physics engine for detailed, efficient rigid body simulations with contacts. mujoco-py allows using MuJoCo from Python 3. This library has been up

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machine-learning Documentation Listings model deployment bandits search time series projects ab tests model selection big data dim reduct recsys trees

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A Flow-based Generative Network for Speech Synthesis

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Keras Applications Keras Applications is the applications module of the Keras deep learning library. It provides model definitions and pre-trained weights for a number of popular archictures, such as VGG16, ResNet50, Xception,

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tensorflow-yolov4-tflite YOLOv4 Implemented in Tensorflow 2.0. Convert YOLO v4, YOLOv3, YOLO tiny .weights to .pb, .tflite and trt format for tensorflow, tensorflow lite, tensorRT. Download yolov4.weights file: https://drive.g

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Databricks
Deep Learning Pipelines for Apache Spark

databricks/spark-deep-learning

Deep Learning Pipelines for Apache Spark Deep Learning Pipelines provides high-level APIs for scalable deep learning in Python with Apache Spark. Overview Building and running unit tests Spark version compatibility S

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Deep neural network to extract intelligent information from PDF invoice documents.

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tensorflow-DeepFM This project includes a Tensorflow implementation of DeepFM [1]. NEWS A modified version of DeepFM is used to win the 4th Place for Mercari Price Suggestion Challenge on Kaggle. See the slide here

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Tools for professional robotic development in C++ and Python with a touch of ROS, autonomous driving and aerospace

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Unsupervised Data Augmentation Overview Unsupervised Data Augmentation or UDA is a semi-supervised learning method which achieves state-of-the-art results on a wide variety of language and vision tasks. With only 20 l

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dtreeviz : Decision Tree Visualization Description A python library for decision tree visualization and model interpretation. By Terence Parr and Prince Grover See How to visualize decision trees for deeper discussio

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Sagar Vinodababu
Show, Attend, and Tell | a PyTorch Tutorial to Image Captioning

sgrvinod/a-PyTorch-Tutorial-to-Image-Captioning

This is a PyTorch Tutorial to Image Captioning. This is the first in a series of tutorials I'm writing about implementing cool models on your own with the amazing PyTorch library. Basic knowledge of PyTorch, convolutional and recurrent ne

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An awesome collection of community detection papers with implementations.

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Daniel Johnson
A recurrent neural network designed to generate classical music.

danieldjohnson/biaxial-rnn-music-composition

Biaxial Recurrent Neural Network for Music Composition This code implements a recurrent neural network trained to generate classical music. The model, which uses LSTM layers and draws inspiration from convolutional neural network

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About Chess reinforcement learning by AlphaGo Zero methods. This project is based on these main resources: DeepMind's Oct 19th publication: Mastering the Game of Go without Human Knowledge. The great Reversi development

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A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API

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swifter A package which efficiently applies any function to a pandas dataframe or series in the fastest available manner. To know about latest improvements, please check changelog. Installation: $ pip install

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Meta Research
Non-local Neural Networks for Video Classification

facebookresearch/video-nonlocal-net

Non-local Neural Networks for Video Classification This code is a re-implementation of the video classification experiments in the paper Non-local Neural Networks. The code is developed based on the Caffe2 framework.

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用Resnet101+GPT搭建一个玩王者荣耀的AI

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Bag of Tricks and A Strong ReID Baseline Bag of Tricks and A Strong Baseline for Deep Person Re-identification. CVPRW2019, Oral. A Strong Baseline and Batch Normalization Neck for Deep Person Re-identification. IEEE Transactions

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null
Codes for paper "Mask Scoring R-CNN".

zjhuang22/maskscoring_rcnn

Mask Scoring R-CNN (MS R-CNN) By Zhaojin Huang, Lichao Huang, Yongchao Gong, Chang Huang, Xinggang Wang. CVPR 2019 Oral Paper, pdf This project is based on maskrcnn-benchmark. Introduction Mask Scoring R-CNN contain

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Visualizing the Loss Landscape of Neural Nets This repository contains the PyTorch code for the paper Hao Li, Zheng Xu, Gavin Taylor, Christoph Studer and Tom Goldstein. Visualizing the Loss Landscape of Neural Nets. NIPS, 20

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Pytorch implementation of the preprint paper "Castle in the Sky: Dynamic Sky Replacement and Harmonization in Videos"

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Awesome NAS A curated list of neural architecture search and related resources. Inspired by awesome-deep-vision, awesome-adversarial-machine-learning, awesome-deep-learning-papers, and awesome-architecture-search. Please feel f

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Deep Learning with TensorFlow 2 and Keras – Notebooks This project accompanies my Deep Learning with TensorFlow 2 and Keras trainings. It contains the exercises and their solutions, in the form of Jupyter notebooks. WARNING: Ten

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Xin Yi
Awesome GAN for Medical Imaging

xinario/awesome-gan-for-medical-imaging

Awesome GAN for Medical Imaging A curated list of awesome GAN resources in medical imaging, inspired by the other awesome-* initiatives. For a complete list of GANs in general computer vision, please visit really-awesome-gan. T

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awesome anomaly detection A curated list of awesome anomaly detection resources. Inspired by awesome-architecture-search and awesome-automl. Last updated: 2020/05/07 What is anomaly detection? Anomaly detection i

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Import public NYC taxi and for-hire vehicle (Uber, Lyft, etc.) trip data into PostgreSQL database

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pycls pycl is an image classification codebase, written in PyTorch. The codebase was originally developed for a project that led to the On Network Design Spaces for Visual Recognition work. pycls has since matured into a gene

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A powerful and intuitive WYSIWYG interface that allows anyone to create Machine Learning models! The concept of AI-Blocs is to have a simple scene with draggable objects that have scripts attached to them. The model can be ru

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TensorFlow Fold TensorFlow Fold is a library for creating TensorFlow models that consume structured data, where the structure of the computation graph depends on the structure of the input data. For example, this model implements

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TensorFlow Fold TensorFlow Fold is a library for creating TensorFlow models that consume structured data, where the structure of the computation graph depends on the structure of the input data. For example, this model implements

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ONNX-TensorRT: TensorRT backend for ONNX

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Ryuichiro Hataya
PyTorch implementation of SENet

moskomule/senet.pytorch

SENet.pytorch An implementation of SENet, proposed in Squeeze-and-Excitation Networks by Jie Hu, Li Shen and Gang Sun, who are the winners of ILSVRC 2017 classification competition. Now SE-ResNet (18, 34, 50, 101, 152/20, 32) an

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UNIT: UNsupervised Image-to-image Translation Networks License Copyright (C) 2018 NVIDIA Corporation. All rights reserved. Licensed under the CC BY-NC-SA 4.0 license (https://creativecommons.org/licenses/by-nc-sa/4.

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ResNeXt: Aggregated Residual Transformations for Deep Neural Networks By Saining Xie, Ross Girshick, Piotr Dollár, Zhuowen Tu, Kaiming He UC San Diego, Facebook AI Research Table of Contents Introduction Citatio

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Masked Autoencoders: A PyTorch Implementation This is a PyTorch/GPU re-implementation of the paper Masked Autoencoders Are Scalable Vision Learners: @

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About PCV PCV is a pure Python library for computer vision based on the book "Programming Computer Vision with Python" by Jan Erik Solem. More details

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The Unsplash Dataset is made up of over 200,000+ contributing global photographers and data sourced from hundreds of millions of searches across a nearly unlimited number of uses and contexts. Due to the breadth of intent and semantics contained within the Unsplash dataset, it enables new opportunities for research and learning.

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A curated list of awesome neural radiance fields papers

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About PyTorch 1.2.0 Now the master branch supports PyTorch 1.2.0 by default. Due to the serious version problem (especially torch.utils.data.dataloader), MDSR functions are temporarily disabled. If you have to train/evaluate the MDSR

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Bihan Wen
Collection of popular and reproducible image denoising works.

wenbihan/reproducible-image-denoising-state-of-the-art

Collection of popular and reproducible image denoising works.

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[CVPR2020] Surpassing MobileNetV3: "GhostNet: More Features from Cheap Operations"

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RoboSat Generic ecosystem for feature extraction from aerial and satellite imagery Berlin aerial imagery, segmentation mask, building outlines, simplified GeoJSON polygons Table of Contents Overview Installa

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Alias-Free Generative Adversarial Networks (StyleGAN3) Official PyTorch implementation of the NeurIPS 2021 paper Alias-Free Generative Adversarial Net

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Aki Vehtari
Bayesian Data Analysis course at Aalto

avehtari/BDA_course_Aalto

Bayesian Data Analysis course material This repository has course material for Bayesian Data Analysis course at Aalto (CS-E5710). Aalto students should check also MyCourses announcements. The course material in the repo can be u

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SnakeAI Download and Run To run the program you will need Processing YouTube Video Snake Neural Network Each snake contains a neural network. The neural network has an input layer of 2

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Notice(2019.11.2) This repo was built back two years ago when there were no pytorch detection implementation that can achieve reasonable performance. At this time, there are many better repos out there, for example: detectron

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RLkit Reinforcement learning framework and algorithms implemented in PyTorch. Implemented algorithms: Skew-Fit example script paper Documentation Requires multiworld to be installed Reinforcement L

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Machine Learning Resources, Practice and Research

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CornerNet-Lite: Training, Evaluation and Testing Code Code for reproducing results in the following paper: CornerNet-Lite: Efficient Keypoint Based Object Detection Hei Law, Yun Teng, Olga Russakovsky, Jia Deng arXiv:1904.08900

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NCRF++: An Open-source Neural Sequence Labeling Toolkit 1. Introduction 2. Requirement 3. Advantages 4. Usage 5. Data Format 6. Performance 7. Add Handcrafted Features 8. Speed 9. N best Decoding 10. Reprod

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SSD: Single-Shot MultiBox Detector implementation in Keras Contents Overview Performance Examples Dependencies How to use it Download the convolutionalized VGG-16 weights Download the original trained

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null
BERT-related papers

tomohideshibata/BERT-related-papers

BERT-related Papers This is a list of BERT-related papers. Any feedback is welcome. Table of Contents Survey paper Downstream task Generation Quality evaluator Modification (multi-task, masking strategy, et

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automl-gs Give an input CSV file and a target field you want to predict to automl-gs, and get a trained high-performing machine learning or deep learning model plus native Python code pipelines allowing you to integrate that mo

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Deep ANPR Using neural networks to build an automatic number plate recognition system. See this blog post for an explanation. Note: This is an experimental project and is incomplete in a number of ways, if you're looking for a p

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Pytorch implementation of RetinaNet object detection.

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A (Heavily Documented) TensorFlow Implementation of Tacotron: A Fully End-to-End Text-To-Speech Synthesis Model Requirements NumPy >= 1.11.1 TensorFlow >= 1.3 librosa tqdm matplotlib scipy

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Resemblyzer allows you to derive a high-level representation of a voice through a deep learning model (referred to as the voice encoder). Given an audio file of speech, it creates a summary vector of 256 values (an embedding, often shortene

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CenterNet: Keypoint Triplets for Object Detection by Kaiwen Duan, Song Bai, Lingxi Xie, Honggang Qi, Qingming Huang and Qi Tian The code to train and evaluate the proposed CenterNet is available here. For more technical details,

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MX Mask R-CNN An MXNet implementation of Mask R-CNN. This repository is based largely on the mx-rcnn implementation of Faster RCNN available here. Main Results Cityscapes Method

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OpenSelfSup is an open source unsupervised representation learning toolbox based on PyTorch.

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FaceForensics++: Learning to Detect Manipulated Facial Images

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This is the implementation of "Scaled-YOLOv4: Scaling Cross Stage Partial Network".

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Table of Contents: Introduction to Torch's Tensor Library Computation Graphs and Automatic Differentiation Deep Learning Building Blocks: Affine maps, non-linearities, and objectives Optimization and Training Creating

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RetinaFace in PyTorch A PyTorch implementation of RetinaFace: Single-stage Dense Face Localisation in the Wild. Model size only 1.7M, when Retinaface use mobilenet0.25 as backbone net. We also provide resnet50 as backbone net to

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ondyari
Github of the FaceForensics dataset

ondyari/FaceForensics/

FaceForensics++: Learning to Detect Manipulated Facial Images Overview FaceForensics++ is a forensics dataset consisting of 1000 original video sequences that have been manipulated with four automated face manipulati

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mljar-supervised Automated Machine Learning mljar-supervised is an Automated Machine Learning python package. It can train ML models for: binary classification, multi-class classification, regression.

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GANimation: Anatomically-aware Facial Animation from a Single Image [Project] [Paper] Official implementation of GANimation. In this work we introduce a novel GAN conditioning scheme based on Action Units (AU) annota

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Dang-Khoa Le Tan
List of AI Residency Programs

dangkhoasdc/awesome-ai-residency

List of AI Residency Programs All year internships: MILA (6 months)[Link] 2020 Uber AI Residency Program [Link] . Application Deadline: Jan 19, 2020. Shell AI Residency Program [Link] . Applicatio

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Implementation of research papers on Deep Learning+ NLP+ CV in Python using Keras, Tensorflow and Scikit Learn.

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Philippe Rémy
Deep Learning model to analyze a large corpus of clear text passwords.

philipperemy/tensorflow-1.4-billion-password-analysis

1.4 Billion Text Credentials Analysis (NLP) Using deep learning and NLP to analyze a large corpus of clear text passwords. Objectives: Train a generative model. Understand how people change their passwords over time: hello

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Documentation Build Status Help Gadfly is a plotting and data visualization system written in Julia. It's influenced heavily by Leland Wilkinson's boo

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Awesome JVM A curated list of awesome JVM low level, performance and non-framework related stuff. Awesome JVM Bytecode Garbage collectors Load tools L

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MMAction Introduction MMAction is an open source toolbox for action understanding based on PyTorch. It is a part of the open-mmlab project developed by Multimedia Laboratory, CUHK. Major Features MMActi

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Ralph Ralph is full-featured Asset Management, DCIM and CMDB system for data centers and back offices. Features: keep track of assets purchases and th

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LaneNet-Lane-Detection Use tensorflow to implement a Deep Neural Network for real time lane detection mainly based on the IEEE IV conference paper "Towards End-to-End Lane Detection: an Instance Segmentation Approach".You can ref

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Fast Wavenet: An efficient Wavenet generation implementation Our implementation speeds up Wavenet generation by eliminating redundant convolution operations. A naive implementation of Wavenet generation is O(2^L), while ours

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Analytical tools for visualizing and understanding the neurons of a GAN

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This guide is designated to anybody with basic programming knowledge or a computer science background interested in becoming a Research Scientist with ? on Deep Learning and NLP.

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YOLOv2 in Keras and Applications This repo contains the implementation of YOLOv2 in Keras with Tensorflow backend. It supports training YOLOv2 network with various backends such as MobileNet and InceptionV3. Links to demo applica

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Pytorch implementation of U-Net, R2U-Net, Attention U-Net, and Attention R2U-Net.

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PyTextRank PyTextRank is a Python implementation of TextRank as a spaCy pipeline extension, used to: extract the top-ranked phrases from text documents infer links from unstructured text into structured data run extractiv

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Easy-to-use,Modular and Extendible package of deep-learning based CTR models with PyTorch.

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FLAML is a Python library designed to automatically produce accurate machine learning models with low computational cost. It frees users from selecting learners and hyperparameters for each learner.

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