irfa50

irfa50's Stars

• matterport/Mask_RCNN

  Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow

  Language:Python24.6k5812.8k11.7k

• opendatalab/PDF-Extract-Kit

  A Comprehensive Toolkit for High-Quality PDF Content Extraction

  Language:Python5k36104334

• divelab/DIG

  A library for graph deep learning research

  Language:Python1.9k31208281

• yassouali/pytorch-segmentation

  :art: Semantic segmentation models, datasets and losses implemented in PyTorch.

  Language:Jupyter Notebook1.7k22144378

• sekilab/RoadDamageDetector

  Language:Jupyter Notebook7484747254

• khanhha/crack_segmentation

  This repository contains code and dataset for the task crack segmentation using two architectures UNet_VGG16, UNet_Resnet and DenseNet-Tiramusu

  Language:Python3691218126

• LeiBAI/AGCRN

  Adaptive Graph Convolutional Recurrent Network

  Language:Python34261582

• qinnzou/DeepCrack

  DeepCrack: Learning Hierarchical Convolutional Features for Crack Detection

  Language:Python24732758

• qinnzou/Robust-Lane-Detection

  Language:Python217113072

• dimitrisdais/crack_detection_CNN_masonry

  This GitHub Repository was produced to share material relevant to the Journal paper "Automatic crack classification and segmentation on masonry surfaces using convolutional neural networks and transfer learning" by D. Dais, İ. E. Bal, E. Smyrou, and V. Sarhosis published in "Automation in Construction".

  Language:Python15261054

• willyhagi/climate-data-science

  Climate Data Science and Earth Observation with Python.

  Language:Jupyter Notebook1291245

• OxWearables/ssl-wearables

  Self-supervised learning for wearables using the UK-Biobank (>700,000 person-days)

  Language:Jupyter Notebook9981023

• Sarthakdtu/Road-Cracks-Detection-Neural-Network-

  A convolutional neural network built using keras to detect cracks on road with 97.5% accuracy.

  Language:Jupyter Notebook423421

• domingomery/visioncolab

  Google colab's for image processing, pattern recognition and computer vision

  414015

• Yuki-11/CSBSR

  Official PyTorch implementation of the paper "Joint Learning of Blind Super-Resolution and Crack Segmentation for Realistic Degraded Images", IEEE Transactions on Instrumentation and Measurement (TIM) 2024. CSBSR is an advanced version of our previous work CSSR [MVA'21].

  Language:Python30225

• msminhas93/FabricDefect

  A weakly annotated fabric defect dataset. Contains 24 512x512 images. Every image has a 512x512 mask. The mask has one rectangular bounding box covering the entire defect but has pixels of fabric without defect. This makes the defect detection task challenging.

  26228

• larrycheungbai/ICIP2016_CNN_Crack_Detection

  Language:Python228117

• ruirangerfan/stereo_pothole_datasets

  Pothole Detection Based on Disparity Transformation and Road Surface Modeling (T-IP)

  Language:MATLAB18205

• leomuckley/Multi-Input-ConvLSTM

  TensorFlow implementation of a Multi-Input ConvLSTM for predicting flood extent.

  Language:Python16215

• AI4Food/AI4FoodDB

  AI4FoodDB stores data from a nutritional intervention on 100 obese and overweight individuals that were monitored using different data acquisition methods.

  15412

• mariam-diab/Automated-Detection-of-Defects-on-Metal-Surfaces-using-Deep-Learning-Techniques-and-Vision-Transform

  The project focuses on utilizing deep learning and transformers to detect defects in metals. Tensorflow has been employed to design the model architecture. Among the various approaches explored, the Inception model, a custom CNN model, and the VIT feature extractor have yielded the most promising results.

  Language:Jupyter Notebook400

• muneebelahimalik/Transformer-MaskRCNN

  Enhanced Mask R-CNN model for apple disease instance segmentation by integrating Transformer's multihead-attention mechanism for improved object detection accuracy.

  Language:Python4301

• Sarthakdtu/CNN-Vs-SVM-

  An analysis and comparison of Convolution Neural Network and Support Vector Machine Model for identifying colored images.

  Language:Jupyter Notebook4100

• Shariqaftab20/Plant-Disease-Prediction-Using-MobileNet

  Plant disease classification using deep learning. Detect plant issues from images using CNNs. Jupyter notebook, model, and dataset included.

  Language:Jupyter Notebook220

• leomuckley/awesome-quantum-machine-learning

  Here you can get all the Quantum Machine learning Basics, Algorithms ,Study Materials ,Projects and the descriptions of the projects around the web

  Language:HTML1100

• leomuckley/Deep-math-machine-learning.ai

  A blog which talks about machine learning, deep learning algorithms and the Math. and Machine learning algorithms written from scratch.

  Language:Jupyter Notebook110

• leomuckley/Hands-On-Reinforcement-Learning-With-Python

  Master Reinforcement and Deep Reinforcement Learning using OpenAI Gym and TensorFlow

  Language:Jupyter Notebook110

• leomuckley/learn-with-other-kaggle-users

  Python code for a Kaggle beginner-friendly competition (top 4% finish)

  Language:Python100

• NamalJayasuriya/RGBD_Processing

  Repository for extracting RGB images, depth images, metadata, and processing of RGBD images for depth filtering, error correction, and 3D reconstruction.

  Language:Python110

• Sarthakdtu/Algo_Ds_Notes

  It is a repository that is a collection of algorithms and data structures with implementation in various languages.

  Language:C++1101