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👋 Hey there!

I'm Nima Vahdat, a graduate research assistant fueled by a deep passion for the realms of Deep Learning and Computer Vision. My journey revolves around unraveling the latest frontiers in these fascinating fields. Together, let's harness the transformative potential of Deep Learning! 🌟👁️🔬

If you're up for collaborating on exciting projects or just want to chat about the amazing world of Deep Learning and Computer Vision, reach out! Let's connect, share ideas, and make meaningful contributions to AI and Vision. 🌍🤝🧠

Nima Vahdat's Projects

deepsnn-framework icon deepsnn-framework

DeepSNN Framework is an advanced tool for building Spiking Neural Networks, developed for deep learning applications. Tailored for modern neural networks, it features a flexible architecture, convolutional layers, and advanced encoding methods.

few-shot-learning icon few-shot-learning

This is the implementation of the approach described in the paper "Few-Shot Learning via Embedding Adaptation with Set-to-Set Functions" by Ye, Han-Jia et al. The proposed approach adapts instance embeddings to the target classification task with a set-to-set function and achieves state-of-the-art results on multiple few-shot learning benchmarks.

image_retrieval_system icon image_retrieval_system

This project presents an advanced image retrieval system that utilizes state-of-the-art deep learning models and techniques. By combining the power of VGG16, CBOW Word2Vec, and a projection network, the system enables accurate retrieval of images from a vast collection based on textual descriptions.

leukemia-cells-segmentation icon leukemia-cells-segmentation

The Leukemia Cells Segmentation project utilizes Genetic and Simulated Annealing algorithms to enhance medical image analysis. Precisely identifying and recoloring common colors in leukemia cell images.

q-learning icon q-learning

Using Q-learning algorithm to solve star and moon problem.

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