A simple guide to a vanilla CNN for regression, potentially useful for engineering applications.
-
Updated
Sep 1, 2020 - Jupyter Notebook
A simple guide to a vanilla CNN for regression, potentially useful for engineering applications.
Emotion recognition with Keras library. Uses AffectNet dataset and valence-arousal labels. Implements CNN architecture with regression
The dataset used for the "A non-contact SpO2 estimation using video magnification and infrared data" publication
Fish scales constitute a valuable source of information about individual life histories, but correctly extracting this information requires a highly skilled expert. Here, we train a deep convolutional neural network architecture EfficientNet B4 on a set of about 9000 salmon scale images, and show that it attains good performance on predicting a …
House price estimation from visual and textual features using both machine learning and deep learning models
This is my first project on Github
This project aims to enhance the quality of low-resolution images by mainly focusing on sharpening the edges of colors in the image; making them sharp and distinctly better quality with some improvement in the overall quality of the image. This will be achieved through Deep Learning.
Facial key-points detection by using CNN model.
A CNN Regression Model for Predicting Age from an Image
INTRA-HOUR SOLAR IRRADIANCE ESTIMATION USING INFRARED SKY IMAGES AND MOBILENETV2-BASED CNN REGRESSION
ENHANCING INTRA-HOUR SOLAR IRRADIANCE ESTIMATION THROUGH KNOWLEDGE DISTILLATION AND INFRARED SKY IMAGES
Finding key points on the face
Implementation of a convolutional neural network for regression and classification tasks
Add a description, image, and links to the cnn-regression topic page so that developers can more easily learn about it.
To associate your repository with the cnn-regression topic, visit your repo's landing page and select "manage topics."