A generative network for animal vocalizations. For dimensionality reduction, sequencing, clustering, corpus-building, and generating novel 'stimulus spaces'. All with notebook examples using freely available datasets.

TensorFlow (Keras) implementation of MobileNetV3 and its segmentation head

ipython notebooks for learning how to use SimpleITK

Este repositorio presenta una implementación de segmentación de mamas utilizando YOLOv8. La segmentación de mamas es crucial en el diagnóstico de cáncer de mama. El proyecto incluye un notebook detallado y una demostración desplegada para probar el modelo en tiempo real.

Computer Vision Paper Reviews with Key Summary of paper, End to End Code Practice and Jupyter Notebook converted papers

Analytics and ML notebooks

This repository utilizes YOLOv8 for object detection and segmentation in images and videos. It does not include any training or fine-tuning; instead, it uses pre-trained models. The implementation is provided in two ways: via command-line execution and Python scripting. To run and use YOLOv8, simply execute the notebook in Google Colab.

Collection of notebooks for image segmentation tasks.

Training and validation tests using 640×640 images (normal mode) versus 160×160 tiles generated from the same images. Comparison of results, metrics, and visualizations.

Scripts & notebooks from the beggining of my Ph.D.

Unets notebook developed while I was working in NUS for multiclass 3D segmentation

Wound healing analysis and segment the wound area

Jupyter notebook for clustering-based user segmentation using EDA and PCA. Includes visualizations, summary stats, and insights for targeted marketing and personalization.

Jupyter Notebooks e codigos para analise de bioimagens e dados biologicos utilizados no meu canal BioPrograma - https://www.youtube.com/channel/UCbJAU7N9FYvwkdgSwD_1S4Q

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

Processing code and exploratory notebooks for BeetlePalooza dataset (2018 NEON Ethanol-preserved Ground Beetles).

Deeplearning (pytorch, transformers, GANs, BERT, RNNs)

This is a repository of my Google Colab notebooks for various machine/deep learning problems.