CNN implementation for medical X-Ray image segmentation

Find logos in images and videos in just one-shot. Never be embarrassed again to say that you have a small data situation!

TensorFlow Input Pipeline Examples based on multi-thread and FIFOQueue

finetune bert for small dataset text classification in a few-shot learning manner using ProtoNet

PyTorch implementation of Sentiment Analysis of the long texts written in Serbian language (which is underused language) using pretrained Multilingual RoBERTa based model (XLM-R) on the small dataset.

Generative Latent Implicit Conditional Optimization when Learning from Small Sample ICPR 20'

Sentiment Analysis of tweets written in underused Slavic languages (Serbian, Bosnian and Croatian) using pretrained multilingual RoBERTa based model XLM-R on 2 different datasets.

Project to scrape CFTC.gov reports and present using Power Query & Power Pivot

AutoML tool for imbalanced and small tabular datasets

Mixture of Experts from scratch

This repository contains Alzheimer's detection model using few-shot learning and a machine learning ensemble model. With limited samples, the few shot learning enables efficient detection and the ensemble model incorporates the advantages of multiple algorithms improving the efficiency of detection.

My solution of dirty/cleaned plates recognition kaggle task

Implements MobileViT and ViT from scratch, compatible with graph execution mode in tensorflow. Compares multiple cnn and transformer-based models including VGG, ResNet, ViT and MobileViT on a small cultrual relic data set.

Experiments with artificial neural networks on small datasets.

Research log for Clastic Music

A deep learning based domain knowledge integration for small dataset

Source code of the Paper "Gohberg-Semencul Toeplitz Covariance Estimation via Autoregressive Parameters"" (IEEE TSP 25)

This project implements Lithology microscopic image classification on Weeds Dataset using transfer learning. It formulates the classification task to a Federated Transfer Learning (FTL) scheme and proposed a Fine-Tuned Aggregation strategy for Federated Learning (FTA-FTL).

Homework on training deep networks with very small data - MVA MSc