Popular GitHub Repositories for Endangered Species

Identify bird sounds in real time with this Android version of BirdNET. Bird sound recognition for more than 6,000 species worldwide.

[ICLR 2024] DNABERT-2: Efficient Foundation Model and Benchmark for Multi-Species Genome

{mvgam} R ? to fit Dynamic Bayesian Generalized Additive Models for multivariate modeling and forecasting

Simplify camera trap image analysis with AI species recognition models based around the MegaDetector model

DNABERT_S: Learning Species-Aware DNA Embedding with Genome Foundation Models

Supervised Classification of bird species :bird: in high resolution images, especially for, Himalayan birds, having diverse species with fairly low amount of labelled data [ICVGIPW'18]

Fish Detection (Segmentation) & Classification models and training scripts

Faster, better, smarter ecological niche modeling and species distribution modeling

Polish bird species recognition - Bird song analysis and classification with MFCC and CNNs. Trained on EfficientNets with final score 0.88 AUC. Women in Machine Learning & Data Science project.

Composition of short musical pieces with reinforcement learning. To be more detailed, framing of fifth species counterpoint writing as an optimization problem.

A set of notebooks as a guide to the process of fine-grained image classification of birds species, using PyTorch based deep neural networks.

The official repository for the paper: Scalable learning for bridging the species gap in image-based plant phenotyping.

An application to automatically recognize birds, specify the species, count and save pictures of them, only by use of one camera and a Raspberry Pi. The images and recorded values are made available online on https://opensensemap.org/.

Flutter App capable of classifying 400 different species of birds using MobileNetV2. Upload an image from Google Drive or your phone gallery to accurately predict the species of the bird.

Engineered a robust deep learning model using Convolutional Neural Networks and TensorFlow to classify 114 bird species based on audio recordings. Model achieved an impressive accuracy of 93.4%, providing valuable insights for conservationists and ecologists in the wildlife & ecological research sectors.

Named Entity Recognition for Disorder, Species, Chemical or Drug, Gene and Protein, Enzyme, Anatomy, Biological Process, Molecular Function, Cellular Component, Pathway and microRNAs.

A comprehensive comparison of multimodal models - llama3.2-vision, minicpm-v, llava-llama3, llava, llava13:b and closed source models for animal classification tasks. This project evaluates various models' performance in classifying 10 different animal species, ranging from common to rare animals.

Fish species classification using machine learning techniques.

Cherokee is a highly endangered Native American language spoken by the Cherokee people. We provide a way to mitigate this issue by providing a Neural Machine Translation System.

ANGELCORE is a radical synthesis of biology, machine learning, and cosmological engineering. It represents a new species of intelligence, an Artificial Angel, birthed from the intersection of human neural substrates.