Pinned Repositories
NOOB-ENTITY-
IBM PROJECT-HEALTHCARE DISEASE PREDICTION MODEL
BMI_CALC
Breast_cancer_detection
Image-classification-using-keras
Password-Protected-door-locking-System-
Buried-threat-detection-using-AI-on-GPR-data
We, Achin and Harekrissna worked as a team to complete the project given to us on Buried threat detection using ground penetrating radar. We applied Deep Learning techniques specifically CNN and transfer learning along with image processing techniques like color thresholding, augmentation and masking to identify the threats hidden underground by analysing the radar data. We implemented the techniques given in the research paper (Some Good Practices for Applying Convolutional Neural Networks to Buried Threat Detection in Ground Penetrating Radar, by Daniël Reichman, Leslie M. Collins, Jordan M)
AssignmentCard
bery
bery_official
blog
pie111's Repositories
pie111/scintilla
pie111/Learn-Datascience-For-Free
pie111/first-contributions
🚀✨ Help beginners to contribute to open source projects
pie111/EmpBackend
pie111/AssignmentCard
pie111/demo_repo
Demo repo for studying git
pie111/Neurofeedback-device-for-stress-management
pie111/GTSP_TEAM_36
pie111/NeuroFeeedback
pie111/py
Repository to store sample python programs for python learning
pie111/NOOB-ENTITY-
IBM PROJECT-HEALTHCARE DISEASE PREDICTION MODEL
pie111/Breast_cancer_detection
pie111/Home-Automation-ESP8266-12E-SCINTILLA-Mark01
Home automation done using custom esp12E board.
pie111/BMI_CALC
pie111/Password-Protected-door-locking-System-
pie111/tutorials
pie111/Image-classification-using-keras
pie111/blog
pie111/pie
pie111/official
pie111/official_web_page
pie111/bery_official
pie111/bery
pie111/Static-website
pie111/hello-world
It is my first project in github
pie111/galada
Galada is an easy and simple blog theme for Jekyll.
pie111/PyNET-PyTorch
Generating RGB photos from RAW image files with PyNET (PyTorch)
pie111/Buried-threat-detection-using-AI-on-GPR-data
We, Achin and Harekrissna worked as a team to complete the project given to us on Buried threat detection using ground penetrating radar. We applied Deep Learning techniques specifically CNN and transfer learning along with image processing techniques like color thresholding, augmentation and masking to identify the threats hidden underground by analysing the radar data. We implemented the techniques given in the research paper (Some Good Practices for Applying Convolutional Neural Networks to Buried Threat Detection in Ground Penetrating Radar, by Daniël Reichman, Leslie M. Collins, Jordan M)
pie111/Smart-Street-Lighting-System-PIC-Microcontroller-16F676
My project for developing a smart street light system. In this project, the street light system, in which lights on when needed and light-off when not needed.