Experiments (Prototypes) for LiSSA -> Now moved to ArDoCo-Core
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Updated
Feb 7, 2024 - Kotlin
Experiments (Prototypes) for LiSSA -> Now moved to ArDoCo-Core
Sketch Recognition on TU Berlin Dataset with pre-trained ConvNets and Transfer Learning
📜 [ACMMM '22] DrawMon: A Distributed System for Detection of Atypical Sketch Content in Concurrent Pictionary Games
Tear open drawing canvases inside Jupyter code. In Python, read the canvases as NumPy image data.
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"
Comparison of Feature Extraction Methods on Free-hand Sketches
📚 A collection of sketch based application papers.
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"
🔍 Can you guess what Magenta's sketch-rnn model is drawing?
Model and Android app for sketch recognition using Google's quickdraw dataset
Recognize hand sketched trusses
Recognize hand drawn Arrow Sketches
Recognizer to determine if a Sketch contains Truss structures
Instant feedback graph recognition and insights framework
Gesture GIS extension for Arc GIS Pro
Recognizer to determine if a gesture or sketch is an arrow or not.
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.
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