TensorFlow (Python API) implementation of Neural Style
-
Updated
Dec 24, 2020 - Python
TensorFlow (Python API) implementation of Neural Style
🔥🔥High-Performance Face Recognition Library on PaddlePaddle & PyTorch🔥🔥
libfaceid is a research framework for prototyping of face recognition solutions. It seamlessly integrates multiple detection, recognition and liveness models w/ speech synthesis and speech recognition.
Offline Handwritten Chinese Character Recognition based on GoogLeNet and AlexNet (With CaffeModel)
HDR image reconstruction from a single exposure using deep CNNs
Unofficial PyTorch implementation of the paper titled "Progressive growing of GANs for improved Quality, Stability, and Variation"
Relation-Shape Convolutional Neural Network for Point Cloud Analysis (CVPR 2019 Oral & Best paper finalist)
Object localization in images using simple CNNs and Keras
Kaggle dogs vs cats solution in Caffe
Implementation of character based convolutional neural network
ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels
用Tensorflow实现的深度神经网络。
DeepCrack: Learning Hierarchical Convolutional Features for Crack Detection
Framework for the reproducible processing of neuroimaging data with deep learning methods
4D Spatio-Temporal Semantic Segmentation on a 3D video (a sequence of 3D scans)
MapleStory Rune Solver with Machine Learning and Computer Vision
Deployed bird classification webapp using Deep Learning, Docker, and Streamlit. Users can go onto the webapp and either upload their own images of birds or select from a set of images to feed through a Deep Learning model and display a prediction.
A Novel Embedding Model for Knowledge Base Completion Based on Convolutional Neural Network (NAACL 2018) (Pytorch and Tensorflow)
Building a HTTP-accessed convolutional neural network model using TensorFlow NN (tf.nn), CIFAR10 dataset, Python and Flask.
Add a description, image, and links to the convolutional-neural-network topic page so that developers can more easily learn about it.
To associate your repository with the convolutional-neural-network topic, visit your repo's landing page and select "manage topics."