JKUAT-SES

jkuatses

A Home where we host engineers to talk about their process and lessons they have learnt on how to make an impact by building cool things

  1. 02.10.2021

    Projects - Image classification episode 14

    Bernice Ngethe reveals how to do image classification. Check out her Twitter handle.  If you want to read up on some of our research, you can check out all our bonus material over at https://github.com/JKUATSES/2021-image-classification Image classification is pattern recognition in image data using algorithms. Two methods may be used: * Deep learning - uses convolution neural networks to progressively extract higher- and higher-level representations of the image content The CNN comprises a stack of modules, each of which performs three operations. 1. Convolution -extracts tiles of the input feature map, and applies filters to them to compute new features, producing an output feature map, or convolved feature (which may have a different size and depth than the input feature map). Convolutions are defined by two parameters: *Size of the tiles that are extracted (typically 3x3 or 5x5 pixels). *The depth of the output feature map, which corresponds to the number of filters that are applied. 2. Rectified Linear Unit (ReLU)- the CNN applies a  transformation to the convolved feature following each convolution operation, in order to introduce nonlinearity into the model 3. Pooling - the CNN downsamples the convolved feature (to save on processing time), reducing the number of dimensions of the feature map, while still preserving the most critical feature information. A common algorithm used for this process is called max pooling. * Transfer learning using pre-trained models In this image classification, both methods were used comparatively and transfer learning had way better performance. REFERENCES * https://medium.com/analytics-vidhya/image-equalization-contrast-enhancing-in-python-82600d3b371c * https://www.mygreatlearning.com/blog/introduction-to-image-pre-processing/ * https://jannik-zuern.medium.com/using-a-tpu-in-google-colab-54257328d7da * https://towardsdatascience.com/image-enhancement-techniques-using-opencv-and-python-9191d5c30d45 * https://machinelearningmastery.com/how-to-control-the-speed-and-stability-of-training-neural-networks-with-gradient-descent-batch-size/ * https://developers.google.com/machine-learning/practica/image-classification/convolutional-neural-networks * https://www.kdnuggets.com/2019/08/introduction-image-segmentation-k-means-clustering.html * https://machinelearningmastery.com/how-to-improve-performance-with-transfer-learning-for-deep-learning-neural-networks/

    41 min

  2. 29.07.2021

    Projects - Electrical Simulation episode 12

    Tinega Chris reveals how to do electrical simulations for your project. Check out his Twitter handle @tinegachris  If you want to read up on some of our research, you can check out all our bonus material over at https://github.com/JKUATSES/2021-electricalSimulation

    31 min

  3. 15.07.2021

    Projects - Digitals signals simulation episode 11

    Kelvin Mwaniki reveals how to build binary phase-shift keying which can be used by Kenya Power. Check out his Twitter handle @mwaniki169  If you want to read up on some of our research, you can check out all our bonus material over at https://github.com/JKUATSES/2021-DSS.

    44 min

  4. 12.07.2021

    ProjectsDiscussion - Artificial Intelligence episode 10

    We are discussing what are Artificial Intelligence Space in Kenya. To aid in our discussion, I have Felix Wanyoike, Bernice Ng’ethe and Gladys Gachoka.

    51 min

  5. 08.07.2021

    Projects - 101 on Image classification episode 9

    In today’s episode, we cover the fundamentals of image classification. Resources from this Episode GitHub link. First notebook Second notebook Third notebook More can be found on the TensorFlow official website

    30 min

  6. 04.07.2021

    Projects - Control theory episode 8

    Everything you need to get you started with the control theory is discussed here. We will cover Introduction into control systems, Types of control systems, PID control, State Space representation, Drone control (example), Self balancing robot (example) and adaptive cruise control (example). Resources:   Types of contro systems:  Introduction to control systems:    State-space represenbtation and controllability:  Thrust vector control for rockets using PID:    Drone flight dynamics:  PID control tuning for self balancing robots:    Inverted pendulum on a cart demostartion:  Control system design for autonomous cars:  Adaptive cruise control:      Adaptive Cruise Control Project Using MATLAB and Arduino Uno Board:  Introduction to fuzzy logic:  I must say this is fun. Jeff Mboya, reveals how to integrate control theory into your projects. Check out his Twitter handle @AnginaMboya. If you want to read up on some of our research, you can check out all our bonus material over at https://github.com/JKUATSES/2021-ControlTheory

    28 min

  7. 25.06.2021

    ProjectsDiscussion - Embedded Systems episode 7

    We are discussing what are embedded systems and how they help us in real life. To aid in our discussion, I have Felix Wanyoike, Bernice Ng’ethe and Gladys Gachoka.

    41 min

  8. 24.06.2021

    Projects - Memory devices and shift registers episode 6

    Every day we encounter memory one way or another. Even our brains works on memories. What are memory devices in the world of embedded systems? Lamoy will help us answer that. Today we will be talking about how to use shift registers and memory devices and also what are they. With this, you can be able to enhance your embedded skills and also learn how to use memory devices in your projects. I must say this is fun. Resources - Digital Principles and Applications by Donald P. Leach and Albert P. Malvino.  - Memories in Arduino - Memories of an Arduino by Adafruit - Digital Electronics: Principles and Integrated Circuits by Anil K. Maini. - Arduino MemoryFree Github repository. Laurine Owino, Lamoy, reveals how to integrate memory devices into your projects. Check out his Twitter handle @cee_lamoy. If you want to read up on some of our research, you can check out all our bonus material over at https://github.com/JKUATSES/2021-memoryDevices

    31 min
Wyświetl wszystko (13)

O programie

A Home where we host engineers to talk about their process and lessons they have learnt on how to make an impact by building cool things

Informacje

  • Twórca
    jkuatses
  • Lata aktywności
    2 tys.
  • Odcinki
    13
  • Klasyfikacja
    Dla wszystkich
  • Prawa autorskie
    © jkuatses
  • Witryna programu
    JKUAT-SES