merveceyhan's Stars
WZMIAOMIAO/deep-learning-for-image-processing
deep learning for image processing including classification and object-detection etc.
spmallick/learnopencv
Learn OpenCV : C++ and Python Examples
recommenders-team/recommenders
Best Practices on Recommendation Systems
thunlp/GNNPapers
Must-read papers on graph neural networks (GNN)
naganandy/graph-based-deep-learning-literature
links to conference publications in graph-based deep learning
ashishpatel26/Tools-to-Design-or-Visualize-Architecture-of-Neural-Network
Tools to Design or Visualize Architecture of Neural Network
louisfb01/best_AI_papers_2021
A curated list of the latest breakthroughs in AI (in 2021) by release date with a clear video explanation, link to a more in-depth article, and code.
weiaicunzai/awesome-image-classification
A curated list of deep learning image classification papers and codes
robi56/Deep-Learning-for-Recommendation-Systems
This repository contains Deep Learning based articles , paper and repositories for Recommender Systems
graph4ai/graph4nlp
Graph4nlp is the library for the easy use of Graph Neural Networks for NLP. Welcome to visit our DLG4NLP website (https://dlg4nlp.github.io/index.html) for various learning resources!
tensorflow/gnn
TensorFlow GNN is a library to build Graph Neural Networks on the TensorFlow platform.
SeongokRyu/Graph-neural-networks
alelab-upenn/graph-neural-networks
Library to implement graph neural networks in PyTorch
danfenghong/IEEE_TGRS_GCN
Danfeng Hong, Lianru Gao, Jing Yao, Bing Zhang, Antonio Plaza, Jocelyn Chanussot. Graph Convolutional Networks for Hyperspectral Image Classification, IEEE Trans. Geosci. Remote Sens., 2021, 59(7): 5966-5978.
johri-lab/Automatic-leaf-infection-identifier
Automatic detection of plant diseases
deeplearningturkiye/pratik-derin-ogrenme-uygulamalari
Çeşitli kütüphaneler kullanılarak Türkçe kod açıklamalarıyla TEMEL SEVİYEDE pratik derin öğrenme uygulamaları.
MarkoArsenovic/DeepLearning_PlantDiseases
Training and evaluating state-of-the-art deep learning CNN architectures for plant disease classification task.
hhaji/Deep-Learning
Course: Deep Learning
jostbr/shallow-water
Python model solving the shallow water equations (linear momentum, nonlinear continuity)
viritaromero/Plant-diseases-classifier
Artificial Intelligence app that detects diseases in plants using a deep learning model
donwany/Graph-and-Social-Network-Analytics
social network analytics
abdulzakrt/WumpusWorld-CSharp
A Wumpus World in c# and prolog with a GUI
gbroques/missionaries-and-cannibals
Python program that solves the Missionaries and Cannibals problem, a toy problem in AI, with iterative deepening search.
brilacasck/wumpus-prolog
Wumpus Implementation in Prolog Language
Bishalsarang/Missionaries-and-Cannibals-Problem
This repository contains the solution to Missionaries and Cannibal Problem using BFS and DFS search.
mfejzer/reviewers_recommendation
Profile based recommendation of code reviewers
Zulfiqar-Ibrahim/Classification-of-Sugar-Beet-Growth-Phases-UsingSynthetic-Data-in-Yolo-v4
In this project, classification system has predicteddifferent growth phases of synthetic images of sugar beet usingstate of an art, real-time object detection model (Yolo v4). Toachieve this task, Blender is used for the creation of sugar beet’s3D models and Unreal Engine 4 for the simulation in differentenvironments.
armeninants/wumpus-world-game-prolog
Wumpus World implementation in SWI-Prolog
esthervogt/cv-crop-detection-sugarbeets
This repo is an extract of our student project at University of Mannheim dealing with crop detection for sugarbeet plants. The dataset used was provided by Nived Chebrolu; Philipp Lottes; Alexander Schaefer; Wera Winterhalter; Wolfram Burgard; Cyrill Stachniss (2017): Agricultural robot dataset for plant classification, localization and mapping on sugar beet fields. In: The International Journal of Robotics Research. DOI: 10.1177/0278364917720510.
soufianeeo/WumpusGame