René's URL Explorer Experiment

Title: GitHub - RTDataScience/models: A collection of pre-trained, state-of-the-art models in the ONNX format · GitHub

Open Graph Title: GitHub - RTDataScience/models: A collection of pre-trained, state-of-the-art models in the ONNX format

X Title: GitHub - RTDataScience/models: A collection of pre-trained, state-of-the-art models in the ONNX format

Description: A collection of pre-trained, state-of-the-art models in the ONNX format - GitHub - RTDataScience/models: A collection of pre-trained, state-of-the-art models in the ONNX format

Open Graph Description: A collection of pre-trained, state-of-the-art models in the ONNX format - RTDataScience/models

X Description: A collection of pre-trained, state-of-the-art models in the ONNX format - RTDataScience/models

Opengraph URL: https://github.com/RTDataScience/models

X: @github

direct link

Domain: github.com

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README	https://github.com/RTDataScience/models
MIT license	https://github.com/RTDataScience/models
	https://github.com/RTDataScience/models#onnx-model-zoo
ONNX	http://onnx.ai
Jupyter notebooks	http://jupyter.org
	https://github.com/RTDataScience/models#models
Usage	https://github.com/RTDataScience/models#usage-
	https://github.com/RTDataScience/models#read-the-usage-section-below-for-more-details-on-the-file-formats-in-the-onnx-model-zoo-onnx-pb-npz-and-starter-python-code-for-validating-your-onnx-model-using-test-data
	https://github.com/RTDataScience/models#vision
Image Classification	https://github.com/RTDataScience/models#image_classification
Object Detection & Image Segmentation	https://github.com/RTDataScience/models#object_detection
Body, Face & Gesture Analysis	https://github.com/RTDataScience/models#body_analysis
Image Manipulation	https://github.com/RTDataScience/models#image_manipulation
	https://github.com/RTDataScience/models#language
Machine Comprehension	https://github.com/RTDataScience/models#machine_comprehension
Machine Translation	https://github.com/RTDataScience/models#machine_translation
Language Modelling	https://github.com/RTDataScience/models#language
	https://github.com/RTDataScience/models#other
Visual Question Answering & Dialog	https://github.com/RTDataScience/models#visual_qna
Speech & Audio Processing	https://github.com/RTDataScience/models#speech
Other interesting models	https://github.com/RTDataScience/models#others
	https://github.com/RTDataScience/models#image-classification-
MobileNet	https://github.com/RTDataScience/models/blob/master/vision/classification/mobilenet
Sandler et al.	https://arxiv.org/abs/1801.04381
ResNet	https://github.com/RTDataScience/models/blob/master/vision/classification/resnet
He et al.	https://arxiv.org/abs/1512.03385
SqueezeNet	https://github.com/RTDataScience/models/blob/master/vision/classification/squeezenet
Iandola et al.	https://arxiv.org/abs/1602.07360
VGG	https://github.com/RTDataScience/models/blob/master/vision/classification/vgg
Simonyan et al.	https://arxiv.org/abs/1409.1556
AlexNet	https://github.com/RTDataScience/models/blob/master/vision/classification/alexnet
Krizhevsky et al.	https://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf
GoogleNet	https://github.com/RTDataScience/models/blob/master/vision/classification/inception_and_googlenet/googlenet
Szegedy et al.	https://arxiv.org/pdf/1409.4842.pdf
CaffeNet	https://github.com/RTDataScience/models/blob/master/vision/classification/caffenet
Krizhevsky et al.	https://ucb-icsi-vision-group.github.io/caffe-paper/caffe.pdf
RCNN_ILSVRC13	https://github.com/RTDataScience/models/blob/master/vision/classification/rcnn_ilsvrc13
Girshick et al.	https://arxiv.org/abs/1311.2524
DenseNet-121	https://github.com/RTDataScience/models/blob/master/vision/classification/densenet-121
Huang et al.	https://arxiv.org/abs/1608.06993
Inception_V1	https://github.com/RTDataScience/models/blob/master/vision/classification/inception_and_googlenet/inception_v1
Szegedy et al.	https://arxiv.org/abs/1409.4842
Inception_V2	https://github.com/RTDataScience/models/blob/master/vision/classification/inception_and_googlenet/inception_v2
Szegedy et al.	https://arxiv.org/abs/1512.00567
ShuffleNet	https://github.com/RTDataScience/models/blob/master/vision/classification/shufflenet
Zhang et al.	https://arxiv.org/abs/1707.01083
ZFNet-512	https://github.com/RTDataScience/models/blob/master/vision/classification/zfnet-512
Zeiler et al.	https://arxiv.org/abs/1311.2901
	https://github.com/RTDataScience/models#domain-based-image-classification-
MNIST-Handwritten Digit Recognition	https://github.com/RTDataScience/models/blob/master/vision/classification/mnist
Convolutional Neural Network with MNIST	https://github.com/Microsoft/CNTK/blob/master/Tutorials/CNTK_103D_MNIST_ConvolutionalNeuralNetwork.ipynb
	https://github.com/RTDataScience/models#object-detection--image-segmentation-
Tiny YOLOv2	https://github.com/RTDataScience/models/blob/master/vision/object_detection_segmentation/tiny_yolov2
Redmon et al.	https://arxiv.org/pdf/1612.08242.pdf
SSD	https://github.com/RTDataScience/models/blob/master/vision/object_detection_segmentation/ssd
Liu et al.	https://arxiv.org/abs/1512.02325
Faster-RCNN	https://github.com/RTDataScience/models/blob/master/vision/object_detection_segmentation/faster-rcnn
Ren et al.	https://arxiv.org/abs/1506.01497
Mask-RCNN	https://github.com/RTDataScience/models/blob/master/vision/object_detection_segmentation/mask-rcnn
He et al.	https://arxiv.org/abs/1703.06870
Redmon et al.	https://arxiv.org/abs/1612.08242
contribute	https://github.com/RTDataScience/models/blob/master/contribute.md
YOLO v3	https://github.com/RTDataScience/models/blob/master/vision/object_detection_segmentation/yolov3
Redmon et al.	https://arxiv.org/pdf/1804.02767.pdf
Tiny YOLOv3	https://github.com/RTDataScience/models/blob/master/vision/object_detection_segmentation/tiny_yolov3
Redmon et al.	https://arxiv.org/pdf/1804.02767.pdf
DUC	https://github.com/RTDataScience/models/blob/master/vision/object_detection_segmentation/duc
Wang et al.	https://arxiv.org/abs/1702.08502
mIOU	https://github.com/RTDataScience/models/blob/master/models/semantic_segmentation/DUC/README.md/#metric
Long et al.	https://people.eecs.berkeley.edu/~jonlong/long_shelhamer_fcn.pdf
contribute	https://github.com/RTDataScience/models/blob/master/contribute.md
	https://github.com/RTDataScience/models#body-face--gesture-analysis-
ArcFace	https://github.com/RTDataScience/models/blob/master/vision/body_analysis/arcface
Deng et al.	https://arxiv.org/abs/1801.07698
Li et al.	https://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Li_A_Convolutional_Neural_2015_CVPR_paper.pdf
contribute	https://github.com/RTDataScience/models/blob/master/contribute.md
Emotion FerPlus	https://github.com/RTDataScience/models/blob/master/vision/body_analysis/emotion_ferplus
Barsoum et al.	https://arxiv.org/abs/1608.01041
Levi et al.	https://www.openu.ac.il/home/hassner/projects/cnn_agegender/CNN_AgeGenderEstimation.pdf
contribute	https://github.com/RTDataScience/models/blob/master/contribute.md
	https://github.com/RTDataScience/models#image-manipulation-
Zhu et al.	https://arxiv.org/abs/1703.10593
contribute	https://github.com/RTDataScience/models/blob/master/contribute.md
Super Resolution with sub-pixel CNN	https://github.com/RTDataScience/models/blob/master/vision/super_resolution/sub_pixel_cnn_2016
Shi et al.	https://arxiv.org/abs/1609.05158
Fast Neural Style Transfer	https://github.com/RTDataScience/models/blob/master/vision/style_transfer/fast_neural_style
Johnson et al.	https://arxiv.org/abs/1603.08155
	https://github.com/RTDataScience/models#speech--audio-processing-
Graves et al.	https://www.cs.toronto.edu/~fritz/absps/RNN13.pdf
contribute	https://github.com/RTDataScience/models/blob/master/contribute.md
Arik et al.	https://arxiv.org/abs/1702.07825
contribute	https://github.com/RTDataScience/models/blob/master/contribute.md
WaveNet: A Generative Model for Raw Audio	https://arxiv.org/abs/1609.03499
contribute	https://github.com/RTDataScience/models/blob/master/contribute.md
	https://github.com/RTDataScience/models#machine-comprehension-
Bidirectional Attention Flow	https://github.com/RTDataScience/models/blob/master/text/machine_comprehension/bidirectional_attention_flow
Seo et al.	https://arxiv.org/pdf/1611.01603
BERT-Squad	https://github.com/RTDataScience/models/blob/master/text/machine_comprehension/bert-squad
Devlin et al.	https://arxiv.org/pdf/1810.04805.pdf
GPT-2	https://github.com/RTDataScience/models/blob/master/text/machine_comprehension/gpt-2
Radford et al.	https://d4mucfpksywv.cloudfront.net/better-language-models/language_models_are_unsupervised_multitask_learners.pdf
	https://github.com/RTDataScience/models#machine-translation-
Bahdanau et al.	https://arxiv.org/abs/1409.0473
contribute	https://github.com/RTDataScience/models/blob/master/contribute.md
Wu et al.	https://arxiv.org/abs/1609.08144
contribute	https://github.com/RTDataScience/models/blob/master/contribute.md
	https://github.com/RTDataScience/models#language-modelling-
Arisoy et al.	https://pdfs.semanticscholar.org/a177/45f1d7045636577bcd5d513620df5860e9e5.pdf
contribute	https://github.com/RTDataScience/models/blob/master/contribute.md
	https://github.com/RTDataScience/models#visual-question-answering--dialog-
Agrawal et al.	https://arxiv.org/pdf/1505.00468v6.pdf
contribute	https://github.com/RTDataScience/models/blob/master/contribute.md
Zhang et al.	https://arxiv.org/pdf/1511.05099.pdf
contribute	https://github.com/RTDataScience/models/blob/master/contribute.md
Goyal et al.	https://arxiv.org/pdf/1612.00837.pdf
contribute	https://github.com/RTDataScience/models/blob/master/contribute.md
Das et al.	https://arxiv.org/abs/1611.08669
contribute	https://github.com/RTDataScience/models/blob/master/contribute.md
	https://github.com/RTDataScience/models#other-interesting-models-
contribute	https://github.com/RTDataScience/models/blob/master/contribute.md
Generative Adversarial Text to image Synthesis	https://arxiv.org/abs/1605.05396
contribute	https://github.com/RTDataScience/models/blob/master/contribute.md
Modeling Long- and Short-Term Temporal Patterns with Deep Neural Networks	https://arxiv.org/pdf/1703.07015.pdf
contribute	https://github.com/RTDataScience/models/blob/master/contribute.md
DropoutNet: Addressing Cold Start in Recommender Systems	http://www.cs.toronto.edu/~mvolkovs/nips2017_deepcf.pdf
contribute	https://github.com/RTDataScience/models/blob/master/contribute.md
Neural Collaborative Filtering	https://arxiv.org/pdf/1708.05031.pdf
contribute	https://github.com/RTDataScience/models/blob/master/contribute.md
A Hierarchical Neural Autoencoder for Paragraphs and Documents	https://arxiv.org/abs/1506.01057
contribute	https://github.com/RTDataScience/models/blob/master/contribute.md
	https://github.com/RTDataScience/models#usage-
	https://github.com/RTDataScience/models#model-visualization
Netron	https://lutzroeder.github.io/Netron
	https://github.com/RTDataScience/models#contributions
contribute	https://github.com/RTDataScience/models/blob/master/contribute.md
	https://github.com/RTDataScience/models#license
MIT License	https://github.com/RTDataScience/models/blob/master/LICENSE
Readme	https://github.com/RTDataScience/models#readme-ov-file
MIT license	https://github.com/RTDataScience/models#MIT-1-ov-file
Activity	https://github.com/RTDataScience/models/activity
Custom properties	https://github.com/RTDataScience/models/custom-properties
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Terms	https://docs.github.com/site-policy/github-terms/github-terms-of-service
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Community	https://github.community/
Docs	https://docs.github.com/
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