📊 Forecast time-series data using LSTM models in PyTorch; generate, train, and visualize predictions with key metrics for accurate insights.
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Updated
Nov 11, 2025 - Python
📊 Forecast time-series data using LSTM models in PyTorch; generate, train, and visualize predictions with key metrics for accurate insights.
🫁 Automate ETT and Carina segmentation on chest radiographs for faster, accurate assessments, improving patient care and treatment efficiency.
A GPU-accelerated library containing highly optimized building blocks and an execution engine for data processing to accelerate deep learning training and inference applications.
Image augmentation extension for the image-dataset-converter library.
Deep Learning for Automatic Pneumonia Detection, RSNA challenge
Allows you to bend an image in 3D space. It is also acceptable to change lighting, shadows and depth of field
Ready-to-use tool for image augmentation
Next-generation Albumentations: dual-licensed for open-source and commercial use
Implements a UNet-based medical image segmentation framework for precise detection of the carina and endotracheal tube tip, supporting automated clinical evaluation of airway placement.
Shuffle PatchMix (SPM) for Source-Free Domain Adaptation (ICIP 2025); patch-shuffle augmentation + confidence-margin pseudo-labels. New SOTA on PACS (+7.3%), strong results on DomainNet-126 and VisDA-C.
An MCP-compatible image augmentation tool powered by Albumentations. Built for Claude, Kiro, and other AI agents.
ML data processing (For Computer Vision)
Local web application providing API and UI for image augmentation, based on the albumentations library
MemeGen is a web application where the user gives an image as input and our tool generates a meme at one click for the user.
The project aimed to push image captioning technology forward by combining recent advances in image recognition and language modeling to generate novel, descriptive captions that go beyond just naming objects and actions
Towards Fully Synthetic Training: Exploring Data Augmentations for Synthetic-to-Measured SAR in Automatic Target Recognition
A deep learning-based image classification project that recognizes hand gestures for Rock, Paper, and Scissors using CNNs. Includes comparison with traditional ML models like SVM, k-NN, and Random Forest.
A Python module implementing "CAP-VSTNet: Content Affinity Preserved Versatile Style Transfer" that allows for modular implementation of style transfer as an image augmentation in deep learning pipelines, with a fully Pytorch-based framework for image and video training and inference.
A python library for instagram filters
Fast and flexible image augmentation library. Paper about the library: https://www.mdpi.com/2078-2489/11/2/125
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