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Schedule Interview NowBeing part of Softaims has allowed me to see the full spectrum of what technology can achieve when guided by empathy, discipline, and creativity. Each assignment, regardless of size, represents an opportunity to bring clarity to complexity and to turn ambitious ideas into tangible outcomes. I’ve come to realize that successful development isn’t just about writing code—it’s about listening carefully, understanding deeply, and designing thoughtfully. Every client brings unique challenges, and I make it a priority to align my work with their goals, ensuring that the end result is both effective and lasting. Softaims fosters an environment where collaboration is not optional—it’s essential. The collective expertise within the team pushes me to think beyond conventional boundaries, to question, refine, and innovate. I believe that this process of shared learning and experimentation is what makes our solutions resilient and impactful. My ultimate goal is to build technology that feels effortless to use yet powerful in function. I approach every task with the mindset that small details can make a big difference. Through continuous refinement and dedication, I aim to contribute to the kind of work that not only serves today’s needs but anticipates tomorrow’s possibilities.
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In this project, I demonstrate how to perform face recognition using the Dlib library and deep learning. I used a pre-trained network provided by Dlib. This network has been trained on a dataset of over 3 million images. The network is called the ResNet-34.
By combining the power of YOLOv8 and DeepSORT, in this project, I show how to build a real-time vehicle tracking and counting system with Python and OpenCV.
I created a comprehensive guide that provides detailed explanations, practical examples, and step-by-step tutorials to help readers master YOLO. It teaches how to train the YOLO model to accurately detect and recognize license plates in images and real-time videos, as well as how to build an end-to-end ANPR system with YOLO from data collection to deployment. The book includes source code, hands-on coding experience, and a step-by-step guide with clear explanations and code examples, allowing readers to gain practical skills that can be applied to real-world projects.
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