Programmer Think

The title is well chosen, and gentlemen are indispensable. A good title can bring more readers. The title is the first thing a potential audience sees before deciding whether to read an article. As a data scientist, I decided to make a model to help me generate these titles using GPT2. data I made a csv file that contains my in medium The bes ...

Lesson 11 convolutional neural network Advanced CNN pytorch learning video - video link of station B: The final collection of PyTorch deep learning practice_ Beep beep beep_ bilibili The following is the video content notes and source code. The notes are purely personal understanding. If there are errors, you are welcome to point them out. 1 ...

Deep learning image classification (11) mobile netv2 network structure In this section, learn about the network structure of MobileNetV2. Learning video from Bilibili , part of the reference description is derived from knowhow Explain MobileNetV2 in detail. 1. Preface MobileNetV2 was proposed by the google team in 2018. Compared with ...

Reproducing AD-NeRF synthesizes face video from audio and face images and shows natural speaking style flyfish Synthesizing facial video sequences driven by high fidelity audio is an important and challenging problem in many applications such as digital human, chat robot and virtual video conference. The speech head generation process is rega ...

1, Introduction to morphology 1 Overview 1.1 basic idea The corresponding shape in the image is measured and extracted by the structural elements with a certain shape, so as to achieve the purpose of image analysis and recognition 1.2 basic operation Expansion, corrosion, opening and closing operation 1.3 fundamentals of Mathematics set theo ...

every blog every motto: You can do more than you think. 0. Preface Simple summary of pyramid pooling module. Nonsense: I'm still picky about food. Hey, 1. Text 1.1 basic concepts Pyramid pool module, that is, pool operation with different scales. For example, the size of the characteristic diagram after pooling is 1 × 1, (regardles ...

Although transformer has very strong learning and modeling ability in CV tasks, it lacks inductive bias like CNN, so transformer's generalization ability is relatively poor compared with CNN. Therefore, if only Transformer Models global information, Without pre training (JFT-300M), transformer is difficult to surpass CNN in performance (without ...

I mentioned it before GNNExplainer But a lot of formulas in the paper are difficult to touch, so I went to GitHub to find some implementations of gnnexpianer DIGIVDetect Gnnexpianer will interpret the diagram from two perspectives: Edge: an edge mask will be generated, which represents the probability of each edge in the graph, and the v ...

catalog: 1. Necessary environment 2.YOLOX installation and model reasoning 3. Train your data set and test 1. Necessary environment My environment is: Windows 10 + Python 3 9+CUDA11. 1+CUDNN8. one point one There are many tutorials on the Internet. This article mainly records the use of YOLOX. (there is a small pit in the installation of ...

At present, there are few visual data about PointNet + + prediction results on the Internet, which are generally direct visual data sets. Here is a code I use Matplotlib to visualize prediction. I hope it can be helpful to you. Principle: Briefly explain the principle of the code. Firstly, we use the network to give the prediction results of ...