DDE-2/Basics-of-CNN.md

@@ -8,12 +8,71 @@ _C. Ates_
 
 ## Basics of CNNs
 
-..
+-[An introduction to Convolutional Neural Networks](https://towardsdatascience.com/an-introduction-to-convolutional-neural-networks-eb0b60b58fd7)
+
+- [A Survey of the Recent Architectures of Deep Convolutional Neural Networks](https://arxiv.org/ftp/arxiv/papers/1901/1901.06032.pdf)
 
 ## How the kernel operation works?
 
 ..
 
+
+## Convolutional Autoencoders
+
+-[Convolutional Autoencoders (CAE) with Tensorflow](https://ai.plainenglish.io/convolutional-autoencoders-cae-with-tensorflow-97e8d8859cbe)
+
+- [Image Noise Reduction I](https://towardsdatascience.com/convolutional-autoencoders-for-image-noise-reduction-32fce9fc1763)
+
+- [Keras - image denoising](https://keras.io/examples/vision/autoencoder/)
+
+-[Pre-Training CNNs Using Convolutional Autoencoders](https://www.ni.tu-berlin.de/fileadmin/fg215/teaching/nnproject/cnn_pre_trainin_paper.pdf)
+
+## Famous CNN Architectures 
+
+- [CNN Literature](https://paperswithcode.com/methods/category/convolutional-neural-networks)
+
+-[Illustrated: 10 CNN Architectures I](https://towardsdatascience.com/illustrated-10-cnn-architectures-95d78ace614d)
+
+-[Illustrated: 10 CNN Architectures II](https://towardsdatascience.com/top-10-cnn-architectures-every-machine-learning-engineer-should-know-68e2b0e07201)
+
+- [AlexNet to EfficientNet](https://theaisummer.com/cnn-architectures/)
+
+- [DenseNet Literature](https://paperswithcode.com/method/densenet)
+
+- [EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks](https://arxiv.org/abs/1905.11946)
+
+- [HRNet](https://paperswithcode.com/method/hrnet)
+
+## YOLO: You Only Look Once
+
+- [What is YOLO?](https://jonathan-hui.medium.com/yolov4-c9901eaa8e61)
+
+- [What is YOLO -- alternative](https://blog.roboflow.com/a-thorough-breakdown-of-yolov4/)
+
+- [YOLO Paper](https://arxiv.org/abs/2004.10934)
+
+- [Darknet Repo](https://github.com/AlexeyAB/darknet#how-to-use-on-the-command-line)
+
+- [How to Perform Object Detection With YOLOv3 in Keras](https://machinelearningmastery.com/how-to-perform-object-detection-with-yolov3-in-keras/)
+
+- [YOLO repo](https://github.com/hunglc007/tensorflow-yolov4-tflite)
+
+- [YOLO v5](https://towardsdatascience.com/how-to-train-a-custom-object-detection-model-with-yolo-v5-917e9ce13208)
+
+- [YOLO pypi.org](https://pypi.org/project/yolov4/)
+
+- [YOLOv4 implementation with Tensorflow 2](https://pypi.org/project/tf-yolov4/)
+
+- [Train a Custom Mobile Object Detection Model with YOLO](https://blog.roboflow.com/how-to-train-a-custom-mobile-object-detection-model/)
+
+- [Anchor Boxes: why important?](https://towardsdatascience.com/anchor-boxes-the-key-to-quality-object-detection-ddf9d612d4f9)
+
+- [Feature Pyramid Networks for Object Detection](https://arxiv.org/pdf/1612.03144.pdf)
+
+## Image Databases and Benchmarks
+
+- [Image Classification on ImageNet: 91% Top Accuracy - 2022](https://paperswithcode.com/sota/image-classification-on-imagenet)
+
 ## Selected CNN Applications
 
 \
@@ -60,4 +119,4 @@ Object localization in images using simple [CNNs ](https://awesomeopensource.com
 
 ## Additional links
 
-..
+- [Computer Vision Lecture](http://cs231n.stanford.edu/)
\ No newline at end of file