Deep learning for freehand sketch object recognition
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Updated
Apr 8, 2017 - Jupyter Notebook
Deep learning for freehand sketch object recognition
A basic education user interface for learning Chinese and practice Chinese handwriting. Sketch recognition techniques were utilized to recognize, evaluate and give feedback to the user's handwriting samples. Feedback is given on both technique (correctness) and vision (beautifulness) sides.
Recognizer to determine if a gesture or sketch is an arrow or not.
Gesture GIS extension for Arc GIS Pro
Instant feedback graph recognition and insights framework
Recognizer to determine if a Sketch contains Truss structures
Recognize hand drawn Arrow Sketches
Recognize hand sketched trusses
Model and Android app for sketch recognition using Google's quickdraw dataset
🔍 Can you guess what Magenta's sketch-rnn model is drawing?
self-supervised learning, deep learning, representation learning, RotNet, temporal convolutional network(TCN), deformation transformation, sketch pre-train, sketch classification, sketch retrieval, free-hand sketch, official code of paper "Deep Self-Supervised Representation Learning for Free-Hand Sketch"
self-supervised learning, deep learning, representation learning, RotNet, temporal convolutional network(TCN), deformation transformation, sketch pre-train, sketch classification, sketch retrieval, free-hand sketch, official code of paper "Deep Self-Supervised Representation Learning for Free-Hand Sketch"
📚 A collection of sketch based application papers.
Comparison of Feature Extraction Methods on Free-hand Sketches
IEEE TNNLS 2021, transformer, multi-graph transformer, graph, graph classification, sketch recognition, sketch classification, free-hand sketch, official code of the paper "Multi-Graph Transformer for Free-Hand Sketch Recognition"
Tear open drawing canvases inside Jupyter code. In Python, read the canvases as NumPy image data.
📜 [ACMMM '22] DrawMon: A Distributed System for Detection of Atypical Sketch Content in Concurrent Pictionary Games
Sketch Recognition on TU Berlin Dataset with pre-trained ConvNets and Transfer Learning
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