Notes on ML - 2024-CMPU9010-GROUP-3/PROJECT GitHub Wiki
- Admin tasks
- Research datasets
- Research pre-trained models
- Set area of research
- Acquire images
- start labelling
- Finish labeling
- Begin model training
- integrate to the rest of the system for INTERIM REPORT presentation deadline
- continue model training & fine tuning
- continue model implementation
- continue model fine tuning
- USER/SYSTEM EVALUATION presentation deadline
- refine model
- finish implementation
- FINAL DEMONSTRATION presentation deadline
- FINAL REPORT deadline
Computer vision is a field in artificial intelligence that uses machine learning and neural networks to allow computer systems to derive meaningful information from visual inputs.
Deep learning is a subset of machine learning that uses deep neural networks to simulate complex decision-making. Convolutional neural networks (CNNs) break images down into pixels, assigns labels and performs convolutions to make predictions about what "it" is seeing.
- LabelImg - Tool for annotating images - Documentation link
- Label Studio - Documentation Link
- Mask R-CNN basic code
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Object detection in Aerial images
This webpage displays a leaderboard that tracks the progress of object detection in aerial images, including the best available model for each dataset, the papers implementing these models as well as code repositories. - Tensorflow object detection tutorial
- Faster R-CNN with Resnet V2 Object detection model
- Transfer learning using Tensorflow Hub (for basic CNN)
- Object Detection using Tensorflow Hub (Kaggle Notebook)
- Intro to TF Hub for Object Detection (Kaggle Notebook)
- Object Detection Made Easy with TensorFlow Hub: Step-by-Step Tutorial
- Parking Space Detection Model Using PyTorch and Super Gradients
- Parking Space Detection Using Deep Learning
- The Complete Guide to Image Preprocessing Techniques in Python
- Deep Learning based Automated Parking Lot Space Detection using Aerial Imagery
- A Context-enriched Satellite Imagery Dataset and an Approach for Parking Lot Detection
- Detecting Parking Spaces in a Parcel using Satellite Images
- Parking Space Inventory from Above: Detection on Aerial Images and Estimation for Unobserved Regions
- A Hybrid Deep Learning CNN-ELM Approach for Parking Space Detection in Smart Cities
- Roadside Parking Spaces Image Classification Using Deep Learning
- Deep Learning-Based Parking Occupancy Detection Framework Using ResNet and VGG-16
- A Comprehensive Survey on Free Parking Space, Road Signs, and Lane Detection
- Real-Time Parking Space Detection and Management with Artificial Intelligence and Deep Learning System
- Hybrid Deep Learning Approach for Efficient Outdoor Parking Monitoring in Smart Cities
- Parking Space Management Through Deep Learning – An Approach for Automated, Low-Cost, and Scalable Real-Time Detection of Parking Space Occupancy
- Research Review on Parking Space Detection Methods
- Satellite parking: a new method for measuring parking occupancy
- Parking Space Detection Model Using PyTorch and Super Gradients
- Vehicle Occurrence-based Parking Space Detection
- Convolutional Neural Networks for Parking slots detection