Unsupervised Image Segmentation With Deep Segmentation Prior
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Updated
Sep 16, 2019 - Jupyter Notebook
Unsupervised Image Segmentation With Deep Segmentation Prior
Building a deep facial recognition application to authenticate into an application. Building a model using Deep Learning with Tensorflow which replicates what is shown in the paper titled Siamese Neural Networks for One-shot Image Recognition.
This repository contains notebooks on different topics across - linear algebra, image classification, language models etc.
Probabilistic programming stuff 2
Presentation and Practical on a popular NLP paper - Language Models are Few-Shot Learners.
A Rust implementation of Siamese Neural Networks for One-shot Image Recognition for benchmarking performance and results.
Code for ICRA2023 paper "GSMR-CNN: An End-to-end Trainable Architecture for Grasping Target Objects from Multi-Object Scenes"
[ON HOLD] A One-shot face recognition system built with OpenCV and PyTorch.
Used CNN based models like ResNet101 and InceptionV3 to classify brain tumors on brain MRI image dataset. Further more, used siamese network for one-shot classification using cosine triple loss and l2 triple loss.
The source code for Multi-Scale Kronecker-Product Relation Networks for Few-Shot Learning
It is the repo I listed my kernels in Kaggle. You can access it in detail from my Kaggle address https://www.kaggle.com/bulentsiyah.
Performing one-shot learning using a triplet network with different triplet selection methods (random and hard).
Implementing one-shot learning using FaceNet
Teaching machines in comparably few shots.
Face Recognition using Siamese(Twin) Network along with Triplet Loss.
A virtual assistant which operates on voice command.
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