Valentyn Sichkar

PhD student

few words about me

An engineer in Control Systems and Robotics, PhD student, working on Computer Vision, Deep Learning, Image Processing, Autonomous Vehicles. Python, C#, HTML, YOLO, CNNs.

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MNIST

Digits

Classification with ConvNet MNIST

CIFAR-10

Image Classification

with Convolutional Neural Networks CIFAR-10

Traffic Signs

Classification

with Convolutional Neural Networks Traffic Sign

About Project

The Project is aimed at testing online and showing experimental results for classification problems. These problems are Digits Classification (MNIST), Image Classification (CIFAR-10), Traffic Signs Classification (GTSRB).


The Project based on Python + ConvNet (CNN) + Flask + Jinja + HTML.

  • MNIST
  • CIFAR-10
  • Traffic Signs

Types of Neural Networks

MNIST : ConvNet
CIFAR-10 : ConvNet
Traffic Signs : ConvNet

  • Join the course to train YOLO v5

    YOLO v5: Label, Train and Test https://www.udemy.com/course/yolo-v5-label-train-and-test

    Have a look at the abilities that you will obtain:
    Run YOLO v5 to detect objects on image, video and in real time by camera in the first lectures.
    Label-Create-Convert own dataset in YOLO format.
    Train & Test both: in your local machine and in the cloud machine (with custom data and by few lines of the code).

    Example of the objects detection by YOLO v5
    YOLO v5 detections

    Concept Map of the YOLO v5 Course
    Concept Map of the YOLO v5 Course

    Join the Course now!
    https://www.udemy.com/course/yolo-v5-label-train-and-test