Seal testing process: Use deep neural networks to extract deep features of seals and learn the similarity between seals. One is similar to oneself and one is not similar to others. 1. Siamese Network The Siamese network is a commonly used deep learning similarity measurement method. It contains two CNN networks that share weights (to […]
Tag: similarity
Image similarity comparison between CLIP and DINOv2
Source: DeepHub IMBA This article is about 2,500 words, and it is recommended to read for 7 minutes This article will explore the advantages and differences between CLIP and DINOv2. There are two main self-supervised models in the field of computer vision: CLIP and DINOv2. CLIP revolutionized image understanding and became a bridge between pictures […]
Binocular stereo vision – disparity map (stereo matching) implementation of three similarity algorithms
Table of Contents Understanding of binocular stereo vision: Polar geometry of parallel views (the second way to implement disparity maps) Image correction (camera calibration) Implementation – similarity matching, disparity calculation Important influencing parameters Lab report discussion section SGBM algorithm example, this effect is better and faster. [Binocular Vision] SGBM Algorithm Application (Python Version)_Luoye Suifeng’s Blog-CSDN […]
Similarity loss summary, pytorch code
Used to constrain image generation as loss. Gradient optimization pytorch structural similarity (SSIM) loss https://github.com/Po-Hsun-Su/pytorch-ssim https://github.com/harveyslash/Facial-Similarity-with-Siamese-Networks-in-Pytorch/blob/master/Siamese-networks-medium.ipynb class ContrastiveLoss(torch.nn.Module): “”” Contrastive loss function. Based on: http://yann.lecun.com/exdb/publis/pdf/hadsell-chopra-lecun-06.pdf “”” def __init__(self, margin=2.0): super(ContrastiveLoss, self).__init__() self.margin = margin def forward(self, output1, output2, label): euclidean_distance = F.pairwise_distance(output1, output2, keepdim = True) loss_contrastive = torch.mean((1-label) * torch.pow(euclidean_distance, 2) + (label) * […]
Application Utility – Video Input using OpenCV and Similarity Measurement OpenCV v4.8.0
Previous tutorial: Reading geospatial raster files using GDAL Next tutorial: Creating a video using OpenCV Original author Bernát Gábor Compatibility OpenCV >= 3.0 Goals Today, owning a digital video recording system has become a common phenomenon. So what you end up dealing with is no longer a batch of images, but a stream of video. […]
[Use [python] to write the code of [Text Similarity Analysis]]
I had a sudden idea and wanted to use Python to calculate the similarity between two texts. Here is a simple Python code example for calculating the similarity between two texts. The TF-IDF algorithm and cosine similarity based on the bag-of-words model are used here to calculate text similarity. Calculate text similarity based on the […]
[openAI text embedding]openai text embedding: semantic similarity/classification and question retrieval
This article first introduces the content of the model introduction in the official document of openai text embedding, and then introduces how to use embedding for classification in the following paper, and conducts code analysis Paper link: A neural network solves, explains, and generates university math problems by program synthesis and few-shot learning at human […]
Face recognition·similarity measurement
Traditional softmax loss shortcoming It only considers whether it is correctly classified and does not consider the intra-class distance. The following algorithms all solve this problem. FaceNet: A Unified Embedding for Face Recognition and Clustering Highlights Metric learning (tripletloss) difficulty The selection of negative samples is as similar as possible to the positive samples (som […]
Graduation project – Design and implementation of text similarity checking algorithm based on word embedding
Using word embeddings to calculate text similarity Introduction Use word embeddings to implement operations such as similarity calculation between texts. Word embedding In natural language processing, the study of characters is often less meaningful than the study of words, because the basic unit of semantics in natural language is words rather than words (the basic […]
Quick calculation of cosine similarity of all sample pairs in PyTorch
PyTorch defines the cosine_similarity function to calculate the cosine similarity between pairs of vectors. However, there is currently no way to calculate the cosine similarity between each pair of vectors in the list. We’ll explore a very simple and effective way to do this in PyTorch. Let’s first look at a formula, which is the […]