Wolfram Computation Meets Knowledge

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76 items

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2D Face Alignment Net Trained on 300W Large Pose Data

Determine the locations of keypoints from a facial image

3D Face Alignment Net Trained on 300W Large Pose Data

Determine the 2D projection of 3D keypoints from a facial image

A

AdaIN-Style Trained on MS-COCO and Painter by Numbers Data

Transfer the style of one image to another image

Ademxapp Model A1 Trained on ADE20K Data

Segment an image into various semantic component classes

Ademxapp Model A1 Trained on Cityscapes Data

Segment an image of a driving scenario into semantic component classes

Ademxapp Model A1 Trained on PASCAL VOC2012 and MS-COCO Data

Segment an image into various semantic component classes

Ademxapp Model A Trained on ImageNet Competition Data

Identify the main object in an image

Age Estimation VGG-16 Trained on IMDB-WIKI and Looking at People Data

Predict a person's age from an image of their face

Age Estimation VGG-16 Trained on IMDB-WIKI Data

Predict a person's age from an image of their face

C

CapsNet Trained on MNIST Data

Identify the handwritten digit in an image

Clinical Concept Embeddings Trained on Health Insurance Claims, Clinical Narratives from Stanford and PubMed Journal Articles

Represent a clinical concept as a vector

Colorful Image Colorization Trained on ImageNet Competition Data

Colorize a grayscale image

ColorNet Image Colorization Trained on ImageNet Competition Data

Colorize a grayscale image

ColorNet Image Colorization Trained on Places Data

Colorize a grayscale image

ConceptNet Numberbatch Word Vectors V17.06

Represent words as vectors

ConceptNet Numberbatch Word Vectors V17.06 (Raw Model)

Represent words as vectors

CREPE Pitch Detection Net Trained on Monophonic Signal Data UPDATED

Track the pitch of a monophonic signal

CycleGAN Apple-to-Orange Translation Trained on ImageNet Competition Data

Turn apples into oranges in a photo

CycleGAN Horse-to-Zebra Translation Trained on ImageNet Competition Data

Turn horses into zebras in a photo

CycleGAN Monet-to-Photo Translation

Turn a Monet-style painting into a photo

CycleGAN Orange-to-Apple Translation Trained on ImageNet Competition Data

Turn oranges into apples in a photo

CycleGAN Photo-to-Cezanne Translation

Turn a photo into a Cezanne-style painting

CycleGAN Photo-to-Monet Translation

Turn a photo into a Monet-style painting

CycleGAN Photo-to-Van Gogh Translation

Turn a photo into a Van Gogh-style painting

CycleGAN Summer-to-Winter Translation

Turn a summertime photo into a wintertime photo

CycleGAN Winter-to-Summer Translation

Turn a wintertime photo into a summertime photo

CycleGAN Zebra-to-Horse Translation Trained on ImageNet Competition Data

Turn zebras into horses in a photo

D

Deep Speech 2 Trained on Baidu English Data

Transcribe an English-language audio recording

Dilated ResNet-105 Trained on Cityscapes Data

Segment an image of a driving scenario into semantic component classes

Dilated ResNet-22 Trained on Cityscapes Data

Segment an image of a driving scenario into semantic component classes

Dilated ResNet-38 Trained on Cityscapes Data

Segment an image of a driving scenario into semantic component classes

E

ELMo Contextual Word Representations Trained on 1B Word Benchmark

Represent words as contextual word-embedding vectors

G

Gender Prediction VGG-16 Trained on IMDB-WIKI Data

Predict a person's gender from an image of their face

GloVe 100-Dimensional Word Vectors Trained on Tweets

Represent words as vectors

GloVe 100-Dimensional Word Vectors Trained on Wikipedia and Gigaword 5 Data

Represent words as vectors

GloVe 200-Dimensional Word Vectors Trained on Tweets

Represent words as vectors

GloVe 25-Dimensional Word Vectors Trained on Tweets

Represent words as vectors

GloVe 300-Dimensional Word Vectors Trained on Common Crawl 42B

Represent words as vectors

GloVe 300-Dimensional Word Vectors Trained on Common Crawl 840B

Represent words as vectors

GloVe 300-Dimensional Word Vectors Trained on Wikipedia and Gigaword 5 Data

Represent words as vectors

GloVe 50-Dimensional Word Vectors Trained on Tweets

Represent words as vectors

GloVe 50-Dimensional Word Vectors Trained on Wikipedia and Gigaword 5 Data

Represent words as vectors

I

Inception V1 Trained on Extended Salient Object Subitizing Data

Count the number of prominent items in an image

Inception V1 Trained on ImageNet Competition Data

Identify the main object in an image

Inception V1 Trained on Places365 Data

Identify the scene type of an image

Inception V3 Trained on ImageNet Competition Data

Identify the main object in an image

L

LeNet Trained on MNIST Data

Identify the handwritten digit in an image

M

Multi-scale Context Aggregation Net Trained on CamVid Data

Segment an image of a driving scenario into semantic component classes

Multi-scale Context Aggregation Net Trained on Cityscapes Data

Segment an image of a driving scenario into semantic component classes

Multi-scale Context Aggregation Net Trained on PASCAL VOC2012 Data

Segment an image into various semantic component classes

O

OpenFace Face Recognition Net Trained on CASIA-WebFace and FaceScrub Data

Represent a facial image as a vector

P

Pix2pix Photo-to-Street-Map Translation

Generate a street map from a satellite photo

Pix2pix Street-Map-to-Photo Translation

Generate a satellite photo from a street map

R

ResNet-101 Trained on Augmented CASIA-WebFace Data

Represent a facial image as a vector

ResNet-101 Trained on ImageNet Competition Data

Identify the main object in an image

ResNet-101 Trained on YFCC100m Geotagged Data

Determine the geolocation of a photograph

ResNet-152 Trained on ImageNet Competition Data

Identify the main object in an image

ResNet-50 Trained on ImageNet Competition Data

Identify the main object in an image

S

Single-Image Depth Perception Net Trained on Depth in the Wild Data

Estimate the depth map of an image

Single-Image Depth Perception Net Trained on NYU Depth V2 and Depth in the Wild Data

Estimate the depth map of an image

Single-Image Depth Perception Net Trained on NYU Depth V2 Data

Estimate the depth map of an image

SqueezeNet V1.1 Trained on ImageNet Competition Data

Identify the main object in an image

U

Unguided Volumetric Regression Net for 3D Face Reconstruction

Reconstruct a 3D facial image from a 2D facial image

V

Vanilla CNN for Facial Landmark Regression

Determine the locations of the eyes, nose and mouth from a facial image

Very Deep Net for Super-Resolution NEW

Increase the resolution of an image

VGG-16 Trained on ImageNet Competition Data

Identify the main object in an image

VGG-19 Trained on ImageNet Competition Data

Identify the main object in an image

W

Wide ResNet-50-2 Trained on ImageNet Competition Data UPDATED

Identify the main object in an image

Wolfram C Character-Level Language Model V1

Generate C code

Wolfram English Character-Level Language Model V1

Generate text in English

Wolfram ImageIdentify Net V1

Identify the main object in an image

Wolfram JavaScript Character-Level Language Model V1

Generate JavaScript code

Wolfram LaTeX Character-Level Language Model V1

Generate LaTeX code

Wolfram Python Character-Level Language Model V1

Generate Python code

Y

Yahoo Open NSFW Model V1

Determine whether an image contains pornographic content

YOLO V2 Trained on MS-COCO Data

Detect and localize objects in an image