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Assessing your cultural and operational fit
Real-Time-Multi-Object-Tracking
July 24, 2025 – July 24, 2025
Real-Time Multi-Object Tracking on Selection with Statistical Analysis, Video recording and Trajectory Plot
View ProjectComputer-Vision-Toolkit
May 10, 2024 – August 11, 2024
This project covers image processing techniques like filtering, edge detection, thresholding, hybrid images, Hough Transform, Active Contours, feature extraction, image matching, segmentation, and face detection and recognition making it a well-rounded toolkit for working with images.
View ProjectAlzheimers-Disease-Prediction
April 26, 2024 – May 26, 2024
This project explores the application of machine learning techniques to detect Alzheimer's disease using MRI scan data. The primary objective is to evaluate different algorithms' effectiveness and improve diagnostic accuracy. The results of this study show promising directions for future research in automated Alzheimer's detection.
View ProjectDigital-Filter-Designer
March 8, 2024 – March 9, 2024
Digital-Filter-Designer — GitHub repository
View ProjectFourier-image-Mixer
March 2, 2024 – March 9, 2024
Fourier-image-Mixer — GitHub repository
View ProjectSBME_DSP_Signal-Equalizer
November 2, 2023 – March 8, 2024
SBME_DSP_Signal-Equalizer — GitHub repository
View ProjectEye_Clinic_Information_System
October 21, 2023 – March 9, 2024
Eye_Clinic_Information_System — GitHub repository
View ProjectCultural Fit Analysis
The candidate's projects show a strong inclination towards technical problem-solving and self-directed learning, which could align with a culture that values innovation and continuous improvement. However, the lack of team-based projects or professional experience makes it difficult to fully assess cultural fit. The projects are diverse within the data science/computer vision domain, but there's no information on collaboration or communication styles.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback provided.