Friday, August 10, 2018

Deep Learning resources for self-study


  1. Biologische Neuronen und technische Neuronenmodelle
  2. Convolutional Neural Networks (CNN)
  3. R-CNN Modell:
    "Rich feature hierarchies for accurate object detection and semantic segmentation"
    Paper

  4. Fast R-CNN Modell:
    "Fast R-CNN"
    Paper
  5. Capsule Networks
    "Dynamic Routing Between Capsules"
    Paper
  6. Deep Learning Bibliotheken
    Crashkurs Deep Learning Bibliotheken: TensorFlow und Keras

  7. Faster R-CNN Modell:
    "Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks"
    Paper
  8. Reservoir Computing: Echo State Networks
  9. Einführung/Crash-Kurs: GPU Programmierung

  10. Yolo und Yolo9000 Modell:
    "You Only Look Once: Unified, Real-Time Object Detection"
    Paper1
    "YOLO9000: Better, Faster, Stronger"
    Paper2
  11. Reservoir Computing: Liquid State Machines
  12. ILSVRC Benchmark
    Imagenet Large Scale Visual Recognition Challenge (ILSVRC): Wie funktioniert der Wettbewerb?
    Link

  13. SSD Modell:
    "Single Shot MultiBox Detector"
    Paper
  14. Generative Adversarial Networks
  15. Deep Learning Bibliotheken
    Crashkurs Deep Learning Bibliotheken: Caffe/Caffe2 sowie Torch/PyTorch

  16. Mask R-CNN Modell:
    "Mask R-CNN"
    Paper
  17. Neuromorphische Chips

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