Deep Learning for Image Enhancement
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Updated
Mar 25, 2023 - Python
Deep Learning for Image Enhancement
For study purposes only, please attribute the source when reprinting.
Callable image enhancement and restoration APIs in Python. Preprocessing experiments and applicators for EyeSea.
The main idea of this project is to learn how to work with convolutional neural networks.
Fast Image Processing with Fully-Convolutional Networks
Restoring image with noise using Python
Official repository for SHDocs: A dataset, benchmark, and method to efficiently generate high-quality, real-world specular highlight data with near-perfect alignment.
Tasks developed for image processing studies, such as image enhancement,
Histogram equalization and contrast stretching without using builtin library functions.
Super Resolution
Distillation of Efficient Dehazing Networks via Soft Knowledge
Codes from the couse of Image Processing (IP) of University of São Paulo (USP).
Keras implementation of LRNN based on Liusifei's work - "Learning Recursive Filters for Low-Level Vision via a Hybrid Neural Network"
Demonstration of the mini-lab component activities conducted for the course of Image Processing (19CCE447).
Critical Analysis and Implementation of SRCNN (part of Deep Learning and Computer Vision module)
Both image and video capable ESRGAN model
RAPID UNDERWATER IMAGE ENHANCEMENT
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