Programming VIP

Image enhancement and model fine tuning learning essay Image enhancement learning objectives Know the common methods of image enhancementAble to use TF Keras to complete image enhancement Large scale data set is the premise of successful application of deep neural network. For example, we can crop the image in different ways to make th ...

I believe that students who study algorithms will learn yoov1 algorithm when they are just getting started with target detection. After all, it is the beginning of YOLO algorithm. Of course, in order to take notes, they will do it directly on this blog for your reference and study. Next, I will share the knowledge required for the implementatio ...

preface: At the Winter Olympics, Gu ailing "soared to the sky", Su Yiming "A blockbuster", the dream team of short track speed skating "forge ahead"... The athletes' spirit of challenging the limit and climbing the peak has aroused the enthusiasm of countless audiences! These athletes who ignite the Winter Olympi ...

Tip: after the article is written, the directory can be generated automatically. Please refer to the help document on the right for how to generate it 1, Data sorting 1. sort If the direction is not indicated in sort, it will be sorted in ascending order by defaultIn multidimensional tensors, sorting is not in the global case, but in t ...

Original text from:< Old cake explanation neural network > catalogue I Normalization and inverse normalization II Practical examples III Complete code example IV Inverse normalization of network expression In order to facilitate better network training, the input and output data will be normalized before training. After training, ...

abstract This example extracts part of the data in the plant seedling data set as the data set. The data set has 12 categories. It demonstrates how to use the VIT image classification model of pytorch version to realize the classification task. Through this article, you can learn: 1. How to build VIT model? 2. How to generate data sets? ...

In the NLP task of automatic text understanding, named entity recognition (NER) is the primary task. The function of NER model is to identify named entities in text corpus, such as person name, organization, location, language and so on.NER model can be used to understand the meaning of a text sentence / phrase. It can recognize the words that ...

Friendly participation: @Cotton cotton YOLO is a target detection method, which is characterized by fast detection and high accuracy. The author regards the target detection task as a regression problem of target region prediction and category prediction. This method uses a single neural network to directly predict the boundary and cate ...

Convolutional neural network (CNN) Learning objectives Understand the composition of convolutional neural networkKnow the principle and calculation process of convolutionUnderstand the function and calculation process of pooling There are two problems in image processing using fully connected neural network: The amount of data to be p ...

Visualization helps to explain and understand the internal structure of deep learning model. Through the visualization of the model calculation diagram, we can find out how the neural network is calculated. The visualization of the model mainly includes the following aspects: How many layers does the model haveInput and output shapes of each l ...