Stalk-Net
Why We're Great >
A generic deep-learning based pipeline for stalk width-estimation. Faster-RCNN based region proposals are used for semantic segmentation of stalks. Stereo Imagery is used to get metric width.
Stalk-Net
Why We're Great >
A generic deep-learning based pipeline for stalk width-estimation. Faster-RCNN based region proposals are used for semantic segmentation of stalks. Stereo Imagery is used to get metric width.
Unsupervised Depth Estimation with GANs
Why We're Great >
A generic deep-learning based pipeline for stalk width-estimation. Faster-RCNN based region proposals are used for semantic segmentation of stalks. Stereo Imagery is used to get metric width.
Stalk-Net
STALK NET: A generic deep-learning based pipeline for stalk width-estimation. Faster-RCNN based region proposals are used for semantic segmentation of stalks. Stereo Imagery is used to get metric width.
Unsupervised Depth Estimation with GANs
Why We're Great >
UNSUPERVISED DEPTH ESTIMATION USING GANS: An Un-Supervised technique that exploits left-right consistency between pairs of stereo image to generate a depth map, that maps left image to right image.
Learning To Drive Using Images
LEARNING TO DRIVE USING IMAGES: An Environment Agnostic architecture that uses Variational Auto Encoders and Proximal Policy Optimization and Soft Actor Critic algorithms to learn policies that drive a car using semantically segmented monocular images.
Learning To Prune Grape Vines
LEARNING TO PRUNE GRAPE VINES: This project explores the use of Deep-RL for pruning grape-vines. A Neural Netwrok policy is trained using Proximal Policy Optimization to reach a pruning location in real time.
Robotic Stalk Grasping
ROBOTIC STALK GRASPING: A Deep-Learning based pipeline to detect grasp-points for taking Penetrometer readings in stereo images of Sorghum Stalks.
Autonomous Navigation in Vineyards
AUTONOMOUS NAVIGATION IN VINEYARDS: An Autonomous system that uses fusion of RTK GPS, Wheel Odometry and IMU data for localization. And uses a LIDAR for obstacle detection and avoidance.