Tarnima S

Intern

RedSky Technologies•  August 2021 - July 2022

1. Led the development of machine learning-based intelligent POS tracking systems, employing Waterfall Methodology. 2. Utilized Microsoft Visio to create detailed process flow charts, enhancing the understanding of project workflows and dependencies. 3. Implemented Jira for efficient project tracking and updates, ensuring streamlined communication and progress monitoring. 4. Collaborated with cross-functional teams, including front-end operations, product management, machine learning model development, and image annotation teams. 5. Worked independently for the Chief Operating Officer, serving as the internal stakeholder for the POS Tracking System.

VIT, Chennai (Vellore Institute of Technology)

Computer Science & Engineering, M.Tech•  July 2020 - July 2022

CSE with Specialisation in Artificial Intelligence and Machine Learning. PROJECTS 1. Detection of COVID19 from Radiography Data-set using Fuzzy-Based CNN (07/2021 - 08/2021) > Developed a model which detects COVID-19 from Radiography Images using Convolutional Neural Network (CNN) and Transfer Learning. > Adopted InceptionResNetV2 and VGG16 Model along with Convolutional Neural Network for improvising the image detection of chest scans used for diagnosing COVID19 pandemic in a person. > Help differentiate between various chest scans that signate various other diseases in a person like Pneumonia and general radiography images. 2. Diagnosis and Treatment of Attention Deficit Hyperactivity Disorder using Artificial Intelligence (09/2020 - 07/2021) > Use of Machine Learning Algorithms for prediction and classification of patients (ADHD or Non-ADHD). > Study on various image classification machine learning algorithms for the image-type data-set used to diagnose ADHD. > Conducting ADHD patient-related surveys for proper procurement of data-set. 3. Image Enhancement using SRGAN (03/2021 - 06/2021) > Reconstructing a high-resolution photo-realistic image from its counterpart low-resolution image using machine learning in computer vision. > Enhancing low-resolution images by applying a deep network with an adversarial network (Generative Adversarial Networks) to produce high-resolution images. > The main target was to reconstruct a super-resolution image or high-resolution image by up-scaling low-resolution image such that texture detail in the reconstructed SR images is not lost. 4. Web-page Visualisation of Data-sets using streamlit_pandas_profiling (02/2021 - 06/2021) > Used pandas_profiling and sweetviz libraries of python to form a report of an uploaded data-set table. > Used streamlit_pandas_profiling to create an application that generates an information visualisation report for an uploaded data-set table. > The report generated was saved in HTML format. 5. Automated Car Parking System (09/2020 - 10/2020) > Organisation and improvisation of traffic and car parking infrastructure. > A proper and detailed collection of data of cars parked in a building with the help of Optical Character recognition. > Data collection done using SQL that stored data and allocated parking spots to the vehicle.