# Computer Vision

* **Multi Layer perceptron (MLP)** for digital classification 
* **CNN (Convolutional Neural Network)** 
  * Filters, Local Receptive fields, parameter sharing 
  * Kernel, stride, padding, pooling 
  * CNN architectures 
    * Alex Net, VGG Net, ResNet, DenseNet 
    * Transfer learning and Fine Tuning 
* **Vision Transformers \[**[**Paper**](https://arxiv.org/pdf/2010.11929)**]**
* **Object Detection** 
  * Bounding Boxes and IOU
  * YOLO (Real time object detection) 
  * Retina Net and Focal Loss 
* **Image Segmentation** 
  * Semantic vs instance segmentation 
    * Metrics - MIoI and Dice coefficient 
  * U-Net, R-CNN, & Mark R-CNN 
* **Advance Object measurement and pose estimation** 
  * counting object via density estimation 
  * image retrieval and search 
  * Auto encoder and GAN
  * Multi model and Image captioning 
* Data Augmentation 
* Training Pipeline
  * Data Parallelism, parallel reads, caching etc,.
* Monitoring and Debugging 

Courses & Reference 

* <https://www.youtube.com/playlist?list=PLPTV0NXA_ZSgmWYoSpY_2EJzPJjkke4Az>
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