CNN for Traffic Signal Recognition System

This project aims to build a CNN from scratch in C++ specifically tailored for traffic signal recognition. By systematically implementing and testing each component, the goal is to create a robust model capable of accurately classifying traffic signals in varying conditions.

Solution Overview

    Learning Foundations

    Mathematics Behind CNNs:

    • Studied and implemented basic linear algebra operations crucial for CNNs, such as convolution, pooling, and backpropagation.

    Understanding CNN Architecture:

    • Researched and comprehended the architecture and functionality of CNNs, especially in the context of image recognition tasks.

Implementation Steps

    Linear Algebra Functions

    • Implemented fundamental operations.
    • Matrix multiplication (dot product).
    • Convolution operations for feature extraction.
    • Activation functions (e.g., ReLU) to introduce non-linearity.

    CNN Components
    Convolutional Layer

    • Developed functions to perform convolution operations on input images using predefined kernels.

    Activation Functions

    • Implemented ReLU activation function to enhance feature representation and improve model performance.

    Pooling Layers

    • Created functions for pooling (e.g., max pooling) to downsample feature maps while retaining essential information.

    Flattening

    • Implemented functions to flatten pooled feature maps into vectors suitable for fully connected layers.

    Backpropagation

    • Developed functions to propagate errors backward through the network, adjusting weights and biases to minimize loss.

    Training and Testing
    Preprocessing:

    • Implemented preprocessing functions for image normalization and augmentation to enhance model robustness.

    Training Function

    • Developed functions to train the CNN using labeled datasets, optimizing model parameters via gradient descent.

    Testing Function

    • Created functions to evaluate the trained CNN on unseen test datasets, measuring performance metrics such as accuracy and recall.

Project Status

    Current State

    • Significant progress made, with core CNN functionalities implemented.

    Remaining Tasks

    • Addressing errors and fine-tuning functions for optimal performance and reliability.

Voice of Appreciation!

Client Success Stories: Empowering Journeys, Amplifying Experiences

Hiren Kotak - Owner - VKJ

Thank you all team for your service above your duty.Really fantastic job guys.Really appreciated for every thing .I worked with many teams for software development, but you guys gave me really gave overwhelming experience. Thank you so much. You guys really gave us experience like a family and friend more than any professional relationship. Thank you so much once again. Keep it up.

Mark - CTO

Great Work Team!💐

A huge thank you to Tuvoc Development Team for the hard work and dedication you’ve shown. Despite the challenges and the occasional weekend urgencies, your resilience and teamwork have been outstanding. It’s a pleasure to sail this long journey with such an amazing team. Here’s to fewer urgencies ahead and continued success together. Truly appreciate all your efforts! Jitendra and Meet. 😇🙏

Ashish P - CTO

We have worked with Jitendra Rathod and his team for over a year now. They are responsible for building and maintaining some critical parts in our customer-facing web applications as well as in the backend application infrastructure. Jitendra and the team have done a great job in adding new features to our web portal in a time-critical manner at a high quality, as well as designed and built a dynamic, highly fault-tolerant backend system that manages complex workloads 24×7 at varying scales.

Justin B - CTO

Tuvoc Technologies has been a huge partner in allowing us to scale out development efforts for our Laravel projects. They have a great mix of left and right brains which creates great synergy between the graphic design and development efforts. They pulled off some very tricky programming feats to get the site to do what we wanted, while not losing sight of the need for superb, modern aesthetics.

Jesper S - CEO

Tuvoc Technologies is an excellent development partner. I have used them on several of my projects, and each time the work has been delivered on time and perfectly. Several times they surprise me with their abilities and deliver better results than I imagined. Communication and delivery speeds are the best I’ve experienced.

Nate W - CTO

Tuvoc Technologies has been a huge partner in allowing us to scale out development efforts for our Laravel projects. They have a great mix of left and right brains which creates great synergy between the graphic design and development efforts. They pulled off some very tricky programming feats to get the site to do what we wanted, while not losing sight of the need for superb, modern aesthetics.

Vivekanand Gopalan - Vice President of Products at Indusface

We have worked with Tuvoc for several years, and they have consistently delivered high-quality work on time. Their diligence, attention to detail, and proactive communication have made them a reliable partner in developing and maintaining our product. We highly recommend Tuvoc for their exceptional service and expertise.

NIR -

I would like to take this opportunity to thank you and thank all the team for your hard work and infinite efforts you put in the Kidum project. We completed this evening the first live launch of the system and from this point the system is live. This couldn’t have done without your work and dedication. Please share my appreciation with the team.

shachar -

Hey team I know that usually it’s just Meet that is speaking here but it’s important to me for everyone to know here – Meet is just freaking AMAZING. He is always available for us, he always makes sure that we are satisfied with the work and changes anything that we don’t feel 100% comfortable with, he is super professional and he is a bubble GOD! We just wanted to say how much we appreciate you Meet and hope to keep working with you forever! thank you so much my friend.

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