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IEEE2mon
A 3D-CNN and LSTM Based Multi-Task Learning Architecture for Action Recognition
Multi-task learning (MTL) is a machine learning method to share knowledge for multiple related machine learning tasks via learning those tasks jointly. It has been shown to be capable of effectively ...
IEEE1d
Multi-Task Learning for Tomato Crop Disease Detection and Severity Estimation using CNN Framework - IEEE Xplore
In this study, the process utilizes convolutional neural networks (CNN) and VGG16 architecture. The determination of disease severity and the stage of the disease is conducted through multi-task ...
GitHub6y
NDDR-CNN, A Simple and General Architecture for General-Purpose CNN based Multi-Task Learning
Codes for ``NDDR-CNN: Layerwise Feature Fusing in Multi-Task CNNs by Neural Discriminative Dimensionality Reduction''. NDDR-CNN is a simple and general architecture for general-purpose CNN based multi ...
GitHub6y
pasrichashivam/hyperface_deep_multi-task-learning_keras_implementation: HyperFace: Deep Multi-task Learning Framework for Face Detection - GitHub
Hyperface model for multi-task learning. Basic model Hyperface is the architecture of AlexNet. Except convolutional layers, remove all fully-connected (Dense) layers. Input each bounding box through ...
Simon Fraser University6y
Architectures, Datasets, and Transfer Learning for CNN-based CAD | Pixels & Predictions - Simon Fraser University
Architectures, Datasets, and Transfer Learning for CNN-based CAD. November 21, 2018 · 3 min · Kumar Abhishek. Paper Title: ... There is a trade-off between using better learning models versus more ...