bunnysaini/Disaster-Classificiation
To prepare an image processing model to classify the type of disaster based on the image dataset.
This dataset contains images for each disaster. Images are placed in folders with disaster name. Images with no damage are also available, for model training purposes. https://www.kaggle.com/varpit94/disaster-images-dataset
This is the face property train code of project face-detection-project
This is the implementation of "Training deep neural networks via direct loss minimization" published at ICML 2016 in PyTorch. The implementation targe
Official Code Implementation of The Paper : XAI for Transformers: Better Explanations through Conservative Propagation For the SST-2 and IMDB expermin
BiMix The code for Bi-Mix: Bidirectional Mixing for Domain Adaptive Nighttime Semantic Segmentation arxiv Framework: visualization results: Requiremen
2048-expectimax Simulating an AI playing 2048 using the Expectimax algorithm The base game engine uses code from here. The AI player is modeled as a m
DeiT: Data-efficient Image Transformers This repository contains PyTorch evaluation code, training code and pretrained models for DeiT (Data-Efficient
PyTorch implementation of [1611.06440 Pruning Convolutional Neural Networks for Resource Efficient Inference] This demonstrates pruning a VGG16 based
Introduction Codebase for the paper Transformer Embeddings of Irregularly Spaced Events and Their Participants. This codebase contains two packages: a
SALT: Stackelberg Adversarial Regularization Code for Adversarial Regularization as Stackelberg Game: An Unrolled Optimization Approach, EMNLP 2021. R
PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place Recognition PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place
Enhancing Knowledge Tracing via Adversarial Training This repository contains source code for the paper "Enhancing Knowledge Tracing via Adversarial T
LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation by Junjue Wang, Zhuo Zheng, Ailong Ma, Xiaoyan Lu, and Yanfei Zh
PAMA This is the Pytorch implementation of Progressive Attentional Manifold Alignment. Requirements python 3.6 pytorch 1.2.0+ PIL, numpy, matplotlib C
Det3D is the first 3D Object Detection toolbox which provides off the box implementations of many 3D object detection algorithms such as PointPillars, SECOND, PIXOR, etc, as well as state-of-the-art
EfficientTTS Unofficial Pytorch implementation of "EfficientTTS: An Efficient and High-Quality Text-to-Speech Architecture"(arXiv). Disclaimer: Somebo
Multi-Time Attention Networks (mTANs) This repository contains the PyTorch implementation for the paper Multi-Time Attention Networks for Irregularly
Semantic Segmentation Easy to use and customizable SOTA Semantic Segmentation models with abundant datasets in PyTorch Features Applicable to followin
JAXMAPP: JAX-based Library for Multi-Agent Path Planning in Continuous Spaces JAXMAPP is a JAX-based library for multi-agent path planning (MAPP) in c
SuRE Evaluation: A Supplementary Material This repository contains supplementary material regarding the evaluations presented in the paper Visual Expl
Python scripts for performing monocular depth estimation using the PackNet-SfM model in ONNX
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