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GitHub6y
Symbol detection in online handwritten graphics using Faster R-CNN
A model is a Faster R-CNN network that takes an image of a handwritten graphic (flowchart or mathematical expression ... The models are implemented using a fork of the the Tensorflow Object Detection ...
IEEE2y
FR-DETR: End-to-End Flowchart Recognition With Precision and Robustness
Existing deep-learning-based object detectors ... for precise and robust flowchart recognition. FR-DETR comprises a CNN backbone and a shared multi-scale Transformer structure to perform symbol ...
Frontiers3y
FPGA-Based CNN for Real-Time UAV Tracking and Detection
Neural networks (NNs) are now being extensively utilized in various artificial intelligence platforms specifically in the area of image classification and real-time object ... detection using a Zynq ...
Scientific Research Publishing7mon
Detection of Cocoa Leaf Diseases Using the CNN-Based Feature Extractor and XGBOOST Classifier ()
The greatest challenge in the fight to eradicate this pandemic remains its early detection ... flowchart. Scenario 3 involves detecting cocoa leaf diseases using feature extractors from VGG19, ...
GitHub2y
Symbol detection in online handwritten graphics using Faster R-CNN
A model is a Faster R-CNN network that takes an image of a handwritten graphic (flowchart or mathematical expression ... The models are implemented using a fork of the the Tensorflow Object Detection ...
IEEE7y
Symbol Detection in Online Handwritten Graphics Using Faster R-CNN
Abstract: Symbol detection ... of using Deep Neural Networks of different complexities as feature extractors. We evaluate the method on publicly available flowchart and mathematical expression (CROHME ...