Responsibilities :

• The objective of the company isto provide GCP based ML solutions.
  • Technologies used: Machine Learning, PyTorch, Python, GCP, Kubernetes, BigQuery, CI/CD.
    

Responsibilities :

• Created Project plan and project requirements.
• Developing Language Models for Non-English languages.

• Develop speech recognition based deskptop application using PyQt

  • Technologies used: PyTorch, Python and Qt.
    

Responsibilities :

• Designed and Developed an end-to-end Deep-Learning based computer vision pipeline to remove densely labelled dataset and convert them into sparsely labelled dataset. The Sparsely Labelled dataset has reduced the training time and computational cost by 32% and is currently used in the project.
• Developed a 2D cubic shape on car images using OpenCV and Python which further used as a label in training a model.
• Developed Qt and C++ based semantic segmentation labelling tool.
• Collaborated with Bosch's Germany team on Autonomous driving project for data visualization and training the VGG network.

• Project management using tools like JIRA to create, assign, and submit tasks, manage task descriptions and task timelines.

• Use SVN for version control.

  • Technologies used: PyTorch, Tensorflow, Python, OpenCV, C++, Qt.
    

Responsibilities:

• Developing novel algorithm for stitching two radiographic images using intensity based image registration method.
• Developed application for human segmentation on thermal images using OpenCV and C++ on RaspberryPi.

• Developed end-to-end deep learning based multiple object detection application for marine environment. The model was trained ande deployed on NVIDA jetson-TK1 development board. The whole application was automated using SHELL scripting on a Linux operating system.

• Developed MATLAB based data labelling tool for cloud and mountain segmentation for France ministry of defense. The dataset was further used as an input for Optical flow algorithm.
• Scrum methodology was followed to keep track of the projects.