Day #197 - Tech Talks and ML based Ideas - Poverty Detection / Slum Detection using Deep Learning

Talk #1 - Neal Jean, " "Combining satellite imagery and machine learning to predict poverty"

Key Summary

• Global Poverty 1.9$ per day
• Need to identify poor people, Surveys are expensive
• Satellite images for classifying locations
• Infer Social-Economic Indicators

• Transfer Learning used for this task

• Learn from where you have more training data
• Nighttime light intensity for economic development

• Gaussian Process on top of CNN

Talk #2 - Using Convolutional Networks and Satellite Imagery to Identify Patterns

Key Summary

• Compare regions within the city
• Intelligent Energy and Infrastructure benchmarking
• Compare various areas of City
• Land Use Classification
• DeepSat Dataset
• Supervised Learning Approach
• pysatml, pysatapi
• VGG16 for Classification
• Pretrain on DeepSat Data and finetune them

Related Work
Slum Segmentation and Change Detection :
Mumbai-slum-segmentation

Next Task
awesome-human-pose-estimation
Human Pose Estimation with TensorFlow
keras-openpose-reproduce
Realtime Multi-Person Pose Estimation
Snagging Parking Spaces with Mask R-CNN and Python

Happy Mastering DL!!!