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Schedule Interview NowMy name is Nikhil T. and I have over 3 years of experience in the tech industry. I specialize in the following technologies: Artificial Neural Network, Deep Neural Network, Data Science Consultation, TensorFlow, Machine Learning, etc.. I hold a degree in Bachelor of Computer Applications, Master of Computer Applications (MCA). Some of the notable projects I've worked on include: Multi-Object Tracking with YOLOv8 and ByteTrack, Human Face Landmark Detection in TensorFlow, Remove Photo Background using Deep Learning in Python, UNET Segmentation on CT Scan Images using TensorFlow, Brain Tumor Segmentation using UNET in TensorFlow, etc.. I am based in Ghaziabad, India. I've successfully completed 6 projects while developing at Softaims.
I thrive on project diversity, possessing the adaptability to seamlessly transition between different technical stacks, industries, and team structures. This wide-ranging experience allows me to bring unique perspectives and proven solutions from one domain to another, significantly enhancing the problem-solving process.
I quickly become proficient in new technologies as required, focusing on delivering immediate, high-quality value. At Softaims, I leverage this adaptability to ensure project continuity and success, regardless of the evolving technical landscape.
My work philosophy centers on being a resilient and resourceful team member. I prioritize finding pragmatic, scalable solutions that not only meet the current needs but also provide a flexible foundation for future development and changes.
Main technologies
3 years
2 Years
2 Years
1 Year
Potentially possible
idiotdeveloper.com
An end-to-end computer vision project for object detection, multi-object tracking, and motion visualization using YOLOv8 and ByteTrack.
In this project, I have used the pre-trained MobileNetv2 for the Human Face Landmark Detection in TensorFlow. For this, I have used the Landmark Guided Face Parsing (LaPa) dataset contains the traini
I have built a python program in this project that removes the background from photos using deep learning. Here, we are using the DeepLabV3+, an image segmentation architecture trained on the human im
In this project, we are going to use CT (computerized tomography) scan data for image segmentation. The dataset consists of pair of images and their annotated binary masks. The images are annotated us
In this project, I have used the UNET architecture for the purpose of brain tumor segmentation in the TensorFlow framework using the Keras API.
Bachelor of Computer Applications in
2014-01-01-2017-01-01
Master of Computer Applications (MCA) in
2022-01-01-2024-01-01