scumechanics

Adventures-in-TensorFlow-Lite

This repository contains notebooks that show the usage of TensorFlow Lite for quantizing deep neural networks.

android_tflite

GPU Accelerated TensorFlow Lite applications on Android NDK. Higher accuracy face detection, Age and gender estimation, Human pose estimation, Artistic style transfer

AndroidML-1-Concrete-Strength-Predictor-App

Anomaly_Detection

awesome-remote-sensing-change-detection

List of datasets, codes, and contests related to remote sensing change detection

awesome-semantic-segmentation

:metal: awesome-semantic-segmentation

Landslide-Susceptibility-Prediction-Using-Machine-Learning-Algorithms

Landslide Susceptibility Prediction and Identification of Most Significant Factors that best describe an area is susceptible to Landslides or not based on Explainable Artificial Intelligence to solve the challenging BlackBox problem of state art Artificial Intelligence based methods.

Landslide_detection_using_Mask_RCNN_new

ML_Projrct_Concrete_Strength_Prediction

Perform These algorithms: - Linear Regression - Lasso Regression - Ridge Regression - Decision Tree Regressor - Random Forest Regressor - KNN Regressor - SVM Regressor AND Pick each of the algorithm and perform These steps: o Split your data between train and test steps. Build your model List down the evaluation metrics you would use to evaluate the performance of the model? Evaluate the model on training data o Predict the response variables for the test data How are the two scores? Are they significantly different? Are they the same? Is the test score better than training score?

XGB-SHAP-concrete-interface-shear-strength

Accurate prediction of the shear strength of the interface between old and new concrete (cold joints) is essential for the design or assessment of precast and retrofitted concrete structures. The XGBoost and Shapley Additive exPlanations technique were used to develop an explainable ML-model for interface shear strength prediction of the cold joints. This package contains the code of the model and the collected database.

scumechanics/Anomaly_Detection

scumechanics/Bearing-Anomaly-Detection-using-Machine-Learning

Showcase how machine learning can help operators monitor equipment conditions through correctly analyzing measurement data collected from many sensors.

scumechanics/clash

scumechanics/ConcreteCrack_Detection

scumechanics/corrosion-monitoring-using-UNET

In order to avoid regulatory violations, downtime, or fatal disasters, industrial assets must be maintained in a timely manner. One of the biggest factors for timely maintenance is corrosion of the assets. Corrosion causes generation of irregular surface that looks bad in appearance and can produce serious problems. To avoid corrosion problems, timely maintenance must be scheduled well in advance. For this, images-based corrosion detection can be a useful tool with respect to real time corrosion tests. In this work, images-based corrosion detection is performed using Deep-learning UNET-8layer architecture. More than 400 images of corrosion data with their binary ground truth or labels are trained to analyze and classify the corroded region in the images. After training, the model is tested, and it is found that the prediction over corroded part of original image data can be done with the model with binary accuracy of 95.28% and validation binary accuracy of 96.87%.

scumechanics/Deep-Learning-High-Entropy-Alloys

High Entropy Alloys (HEAs) are multi-chemical elements alloys with exceptional physical properties. HEAs have sparked the interest in engineering applications such as energy storage, catalysis and bio/plasmonic imaging. The understanding of the structural of composition of HEAs is paramount for the appropriate tuning of their properties. Scanning Transmission Electron Microscopy (STEM) is typically used to acquire images of various materials at the atomic scale resolution. including HEAs. In this repository it is demonstrated how computer vision analysis based on Deep Learning (DL) could be used to extract structural information from STEM images of HEAs. In particular a Fully Convolutional Neural Network (FCN) is trained to recognize the number of atoms of different chemical species in the atomic columns of HEA (i.e., column heights CHs) through semantic segmentation of simulated and experimental STEM images. As a benchmark case, equiatomic PtNiPdCoFe HEAs are considered. This project represent a first attempt for the identification of chemical species in 3D materials. Thus, in addition to the estimation of the structural properties of HEAs, this work establish an advancement of DL applied to microscopy image which could be useful for a broad area of nano-science applications.

scumechanics/GPR-Object-Detection

This repository contains code to train object detection models like FRCNN for identifying objects in Ground Penetrating Radar scans. It also contains code to generate fake data using GANs.

scumechanics/Image_segmentation_with_U-net

Image segmentation using vanilla Unets with batch normalization.

scumechanics/Rainfall_predictor

Use rainfall data predict landslide occur or not

scumechanics/similarity_measures

Quantify the difference between two arbitrary curves in space

scumechanics/ThymeBoost

Forecasting with Gradient Boosted Time Series Decomposition

scumechanics/2022-Project---Carotid-Artery-Screening-by-Wireless-Handheld-Ultrasound

scumechanics/android-demo-app

PyTorch android examples of usage in applications

scumechanics/google-research

Google Research

scumechanics/GroundingDINO

The official implementation of "Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection"

scumechanics/Impeller-stress-prediction

Calculate stress and natural frequency of centrifugal fan's impeller

scumechanics/LLDE

This is the code repo of our ICIP2023 work that proposes a novel approach to low-light image enhancement using the diffusion model (LLDE).

scumechanics/low-light-segmentation-with-mirnet-yolov8-segment-anything

scumechanics/notebooks

Set of Jupyter Notebooks linked to Roboflow Blogpost and used in our YouTube videos.

scumechanics/pykan

Kolmogorov Arnold Networks

scumechanics/RBF-Topology-Optimization

scumechanics/Research-on-Solving-Partial-Differential-Equations-of-Solid-Mechanics-Based-on-PINN

This is the code of my master thesis.

scumechanics/Rheology_PINNs

Repository holding the physics informed machine learning codes to characterize unknown rheology of thermal greases

scumechanics/segment-anything

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

scumechanics/vibrations-of-mindlin-plates

A collection of Python codes to find the natural frequencies of Reissner-Mindlin (thick) plates.

scumechanics/Visualize-Yolo-annotations

A simple tool that will help visualize bounding boxes in darknet/yolo format

scumechanics/X-AnyLabeling

Effortless data labeling with AI support from Segment Anything and other awesome models.

scumechanics/yolov5

YOLOv5 in PyTorch > ONNX > CoreML > iOS

scumechanics/yolov7

Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors

scumechanics/Yolov8-ONNXRuntime