Fully Convolutional DenseNet (A.K.A 100 layer tiramisu) for semantic segmentation of images implemented in TensorFlow.
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Updated
Dec 21, 2018 - Python
Fully Convolutional DenseNet (A.K.A 100 layer tiramisu) for semantic segmentation of images implemented in TensorFlow.
Desktop notifications, the UNIX way
Deep Convolutional Neural Networks for Semantic Segmentation of Multi-Band Satellite Images
An example of semantic segmentation on iOS using CoreML and Keras.
A cost model for compiler performance optimization using deep learning.
Sample for Quick Settings placement API(Android 13+)
This repository contains few Convolution based networks implemented for detecting cilia which is completed on CSCI 8360, Data Science Practicum at the University of Georgia, Spring 2018.
Android 13 Device Tree for Realme XT (RMX1921) - RUI 2.0 Firmware Base
Sample for Photo picker (Android 13+)
Semantic Segmentation on Cilia Images Using Tiramisu Network in PyTorch.
Sample for Themed app icons(Android 13+)
Sample for RuntimeShader API(Android 13+)
Simple notifications from tiramisu in polybar or waybar
Identifies Salt Deposits by analyzing subsurface images.
A notification client for tiramisu written in bash
Reinforcement learning for compiler performance optimization.
Implemented Tiramisu network using pytorch.
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