2024-1 Artificial Intelligence II Project, Industrial University of Santander. Facial recognition and face comparison model using the YOLOv3 algorithm and Siamese networks.
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Updated
Jul 9, 2024
2024-1 Artificial Intelligence II Project, Industrial University of Santander. Facial recognition and face comparison model using the YOLOv3 algorithm and Siamese networks.
Deep Siamese convolutional neural net for biometric authentication of palm print images
Signature verification using a siamese neural network and pytorch.
Analysis of Glyph and Writing System Similarities using Siamese Neural Networks
Dimensionality reduction in very large datasets using Siamese Networks
Siamese Neural Network used for signature verification with three different datasets
Twin Neural Network Training with PyTorch and fast.ai and its Deployment with TorchServe on Amazon SageMaker
RIVF 2021: Deep neural network based learning to rank for address standardization
Official Code for "Registration Quality Evaluation Metric with Self-Supervised Siamese Networks"
This project is to authentication the pen tab based signatures which involves the pen pressure pen tip position etc.
OneShot Learning-based hotword detection.
This project implements a Siamese Neural Network for efficient image triplet analysis, seamlessly integrating OpenCV for image collection. Three categories of images - positive, negative, and anchor - are collected using OpenCV and preprocessed to standardize dimensions to 100x100 pixels in JPEG format.
Facial recognition attendance system
An authentication system that uses a Siamese neural network to compare fingerprint scans.
This is a face verification application made using Siamese Neural Network.
Writer independent offline signature verification using convolutional siamese networks
Calculation of image similarity using siamase neural networks
Implementation of the following papers: Rádli, Richárd, Zsolt Vörösházi, and László Czúni. "Multi-Stream Pill Recognition with Attention." "Pill Metrics Learning with Multihead Attention" and "Word and Image Embeddings in Pill Recognition"
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