Pinned Repositories
SpectralNET
Hyperspectral Image (HSI) classification using Convolutional Neural Networks (CNN) is widely found in the current literature. Approaches vary from using SVMs to 2D CNNs, 3D CNNs, 3D-2D CNNs. Besides 3D-2D CNNs and FuSENet, the other approaches do not consider both the spectral and spatial features together for HSI classification task, thereby resulting in poor performances. 3D CNNs are computationally heavy and are not widely used, while 2D CNNs do not consider multi-resolution processing of images, and only limits itself to the spatial features. Even though 3D-2D CNNs try to model the spectral and spatial features their performance seems limited when applied over multiple dataset. In this article, we propose SpectralNET, a wavelet CNN, which is a variation of 2D CNN for multi-resolution HSI classification. A wavelet CNN uses layers of wavelet transform to bring out spectral features. Computing a wavelet transform is lighter than computing 3D CNN. The spectral features extracted are then connected to the 2D CNN which bring out the spatial features, thereby creating a spatial-spectral feature vector for classification. Overall a better model is achieved that can classify multi-resolution HSI data with high accuracy. Experiments performed with SpectralNET on benchmark dataset, i.e. Indian Pines, University of Pavia, and Salinas Scenes confirm the superiority of proposed SpectralNET with respect to the state-of-the-art methods.
Business-Analysis-With-R
DS4B 101-R: Business Analysis With R 💼 | Business Science University | Matt Dancho
Daily-Coding-Challenges
This repository contains my solutions to various coding challenges that I do every day to improve my programming skills and learn new concepts. Feel free to browse, comment, or fork my code. Happy coding!
data-modeling-with-postgres
Udacity Data Engineering Nanodegree - Project 1 - Data modeling with Postges
Data-Structures-Using-Python
DataEngineering
Data Engineering is the foundation for the new world of Big Data. Enroll now to build production-ready data infrastructure, an essential skill for advancing your data career.
Deep-Learning
Deep Learning 🧠 | Coursera | Deep Leanrning.AI | Andrew Ng
I2DL-TUM
Deep Learning WS2021 🧠 | TUM | Prof. Matthias Nießner
PySyft
A library for answering questions using data you cannot see
Python-For-Everybody
Python For Everybody 👨🏻💻 | Coursera | University of Michigan | Charles Russell Severance
utkarshtrehan's Repositories
utkarshtrehan/Business-Analysis-With-R
DS4B 101-R: Business Analysis With R 💼 | Business Science University | Matt Dancho
utkarshtrehan/I2DL-TUM
Deep Learning WS2021 🧠 | TUM | Prof. Matthias Nießner
utkarshtrehan/Deep-Learning
Deep Learning 🧠 | Coursera | Deep Leanrning.AI | Andrew Ng
utkarshtrehan/PySyft
A library for answering questions using data you cannot see
utkarshtrehan/Daily-Coding-Challenges
This repository contains my solutions to various coding challenges that I do every day to improve my programming skills and learn new concepts. Feel free to browse, comment, or fork my code. Happy coding!
utkarshtrehan/data-modeling-with-postgres
Udacity Data Engineering Nanodegree - Project 1 - Data modeling with Postges
utkarshtrehan/Data-Structures-Using-Python
utkarshtrehan/DataEngineering
Data Engineering is the foundation for the new world of Big Data. Enroll now to build production-ready data infrastructure, an essential skill for advancing your data career.
utkarshtrehan/Python-For-Everybody
Python For Everybody 👨🏻💻 | Coursera | University of Michigan | Charles Russell Severance
utkarshtrehan/for-the-badge
Badges for badges' sake.
utkarshtrehan/jina
Cloud-native neural search framework for 𝙖𝙣𝙮 kind of data
utkarshtrehan/Natural-Language-Processing
utkarshtrehan/React-CustomerDetails
utkarshtrehan/scikit-learn
scikit-learn: machine learning in Python
utkarshtrehan/SpectralNET
utkarshtrehan/utkarshtrehan
utkarshtrehan/utkarshtrehan.github.io