Official implementation of "Extreme Value Meta-Learning for Few-Shot Open-Set Recognition of Hyperspectral Images" (TGRS'23)
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Updated
Aug 15, 2023 - Jupyter Notebook
Official implementation of "Extreme Value Meta-Learning for Few-Shot Open-Set Recognition of Hyperspectral Images" (TGRS'23)
Tensorflow implementation of NIPS 2017 Paper "Prototypical Networks for Few-shot Learning"
Comprehensive Study of Soft Prompting as a efficient method for Model Adaptation
This code is for the honour thesis developed by Dannong Xu. It includes CTNet (developed algorithm in the thesis), Siamese Network, MAML, and Reptile.
Few-shot image classification based on CADA-VAE, using cosine similarity to align two modal features.
COVID-19 Question Dataset from the paper "What Are People Asking About COVID-19? A Question Classification Dataset"
Few-shot learning project: Semantic segmentation of COVID-19 infection in CT scans
Face Recognition System (multiple faces - recognition from images/live camera )
Lowshot learning with Tensorflow
Dementia Prediction by Khalil El Asmar, Fatima Abu Salem, Hiyam Ghannam, Roaa Al-Feel
Adversarial Feature Hallucination in a Supervised Contrastive Space for Few-Shot Learning of Provenance in Paintings
This project investigates few-shot learning for relation extraction using the FewRel dataset. We will compare Prototypical Networks, MAML, and k-NNs in different few-shot settings to see which performs best with minimal data. The goal is to improve relation extraction in NLP by effectively handling data scarcity.
Code for "Improved Few-Shot Visual Classification"
Notes about information extraction with Large Language Models (LLMs)
This is my todo list and some useful materials
Few Shot Learning on Graphs
A unified deeplearning approach for recognising products in retail environments
Effortlessly perform sentiment analysis, translation, speech synthesis, summarization, and Q&A tasks with an interactive UI using prompt engineering
Designed an AI-driven retail platform for a t-shirt store, leveraging LLM capabilities.
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