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followers: 2.0 following: 3.0 repos: 181.0 gists: 1.0

Name: Nicholas Ho

Type: User

Bio: Third-rate scientist proficient in five languages

Location: China

Nicholas Ho's Projects

cnn-explainer

Learning Convolutional Neural Networks with Interactive Visualization. https://poloclub.github.io/cnn-explainer/

cnn_compression

Code repository for our paper "Coreset-Based Neural Network Compression", published in ECCV 2018

confusion

Code for the ECCV 2018 paper "Pairwise Confusion for Fine-Grained Visual Classification"

convnetdraw

Draw multi-layer neural network in your browser

crop-and-label

A script for manually cropping and labeling images

csrnet

CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes

csrnet-pytorch

CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes

cub

CUB is a flexible library of cooperative threadblock primitives and other utilities for CUDA kernel programming.

curriculumnet

CurriculumNet: Weakly Supervised Learning from Large-Scale Web Images

deepem-for-weakly-supervised-detection

MICCAI18 DeepEM: Deep 3D ConvNets with EM for Weakly Supervised Pulmonary Nodule Detection

deeplung

WACV18 paper "DeepLung: Deep 3D Dual Path Nets for Automated Pulmonary Nodule Detection and Classification"

deepseed-3d-convnets-for-pulmonary-nodule-detection

DeepSEED: 3D Squeeze-and-Excitation Encoder-Decoder ConvNets for Pulmonary Nodule Detection

densesharp

3D Deep Learning from CT Scans Predicts Tumor Invasiveness of Subcentimeter Pulmonary Adenocarcinomas

detectors

DetectoRS: Detecting Objects with Recursive Feature Pyramid and Switchable Atrous Convolution

detr

End-to-End Object Detection with Transformers

dplayer

:lollipop: Wow, such a lovely HTML5 danmaku video player

dpp

Detail-Preserving Pooling in Deep Networks (CVPR 2018)

dsb17_3d_lung_nodule_classifier

3d convnet for the classification of nodules/tumor in lung CT scans. Trained on Luna16 for Kaggle's 2017 data science bowl competition (result in top 3%)

dsb2017

The solution of team 'grt123' in DSB2017

early-detection-of-lung-cancer-using-machine-learning

Early detecting of lung cancer using the Luna data set with LIDC IDRI annotations using two models nodule classification"Googlent model" and the malignancy classification "Lenet model". This was for kaggle's Data science bowl 2017.

efficientdet

(Pretrained weights provided) EfficientDet: Scalable and Efficient Object Detection implementation by Signatrix GmbH

efficientdet-1

EfficientDet (Scalable and Efficient Object Detection) implementation in Keras and Tensorflow

face-aging-caae

Age Progression/Regression by Conditional Adversarial Autoencoder

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