Imagen de Portada

bacpipe: a Python package to make bioacoustic deep learning models accessible

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Kather, Vincent S., Haupert, Sylvain, Ghani, Burooj, Stowell, Dan
Formato:	Preprint
Publicado:	2026
Materias:	Machine Learning Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Clustering and novel class recognition: evaluating bioacoustic deep learning feature extractors
por: Kather, Vincent S., et al.
Publicado: (2025)

InsectSet459: an open dataset of insect sounds for bioacoustic machine learning
por: Faiß, Marius, et al.
Publicado: (2025)

Generalization in birdsong classification: impact of transfer learning methods and dataset characteristics
por: Ghani, Burooj, et al.
Publicado: (2024)

Computational bioacoustics with deep learning: a review and roadmap
por: Stowell, Dan
Publicado: (2021)

Sex and age determination in European lobsters using AI-Enhanced bioacoustics
por: Domingos, Feliciano Pedro Francisco, et al.
Publicado: (2025)

Leveraging tropical reef, bird and unrelated sounds for superior transfer learning in marine bioacoustics
por: Williams, Ben, et al.
Publicado: (2024)

First-of-its-kind AI model for bioacoustic detection using a lightweight associative memory Hopfield neural network
por: Gascoyne, Andrew, et al.
Publicado: (2025)

survex: an R package for explaining machine learning survival models
por: Spytek, Mikołaj, et al.
Publicado: (2023)

pyrtklib: An open-source package for tightly coupled deep learning and GNSS integration for positioning in urban canyons
por: Hu, Runzhi, et al.
Publicado: (2024)

Spatiotemporal deep learning models for detection of rapid intensification in cyclones
por: Sutar, Vamshika, et al.
Publicado: (2025)

Towards modeling evolving longitudinal health trajectories with a transformer-based deep learning model
por: Moen, Hans, et al.
Publicado: (2024)

Analogy making as amortised model construction
por: Nagy, David G., et al.
Publicado: (2025)

A redescription mining framework for post-hoc explaining and relating deep learning models
por: Mihelčić, Matej, et al.
Publicado: (2025)

Extreme value forecasting using relevance-based data augmentation with deep learning models
por: Hua, Junru, et al.
Publicado: (2025)

Memorization in deep learning: A survey
por: Wei, Jiaheng, et al.
Publicado: (2024)

Explainable deep learning improves human mental models of self-driving cars
por: Kenny, Eoin M., et al.
Publicado: (2024)

DeepLogit: A sequentially constrained explainable deep learning modeling approach for transport policy analysis
por: Oon, Jeremy, et al.
Publicado: (2025)

Efficiency optimization of large-scale language models based on deep learning in natural language processing tasks
por: Mei, Taiyuan, et al.
Publicado: (2024)

Recent advances in deep learning and language models for studying the microbiome
por: Yan, Binghao, et al.
Publicado: (2024)

Preventing overfitting in deep learning using differential privacy
por: Khatri, Alizishaan Anwar Hussein
Publicado: (2026)

pUniFind: a unified large pre-trained deep learning model pushing the limit of mass spectra interpretation
por: Zhao, Jiale, et al.
Publicado: (2025)

A comparative study of deep learning and ensemble learning to extend the horizon of traffic forecasting
por: Zheng, Xiao, et al.
Publicado: (2025)

Reducing self-supervised learning complexity improves weakly-supervised classification performance in computational pathology
por: Lenz, Tim, et al.
Publicado: (2024)

Economic span selection of bridge based on deep reinforcement learning
por: Zhang, Leye, et al.
Publicado: (2024)

In value-based deep reinforcement learning, a pruned network is a good network
por: Obando-Ceron, Johan, et al.
Publicado: (2024)

A deep learning and machine learning approach to predict neonatal death in the context of São Paulo
por: Raihan, Mohon, et al.
Publicado: (2025)

Integrating remote sensing data assimilation, deep learning and large language model for interactive wheat breeding yield prediction
por: Yang, Guofeng, et al.
Publicado: (2025)

Can neural networks do arithmetic? A survey on the elementary numerical skills of state-of-the-art deep learning models
por: Testolin, Alberto
Publicado: (2023)

Optimization of geological carbon storage operations with multimodal latent dynamic model and deep reinforcement learning
por: Wang, Zhongzheng, et al.
Publicado: (2024)

Automated data curation for self-supervised learning in underwater acoustic analysis
por: Hummel, Hilde I, et al.
Publicado: (2025)

Guaranteed prediction sets for functional surrogate models
por: Gray, Ander, et al.
Publicado: (2025)

Designing a double deep reinforcement learning selection tool for resilient demand prediction
por: Benziane, Bilel Abderrahmane, et al.
Publicado: (2026)

Training instability in deep learning follows low-dimensional dynamical principles
por: Zhang, Zhipeng, et al.
Publicado: (2026)

An efficient deep reinforcement learning environment for flexible job-shop scheduling
por: Wu, Xinquan, et al.
Publicado: (2025)

On the consistency of hyper-parameter selection in value-based deep reinforcement learning
por: Obando-Ceron, Johan, et al.
Publicado: (2024)

Recursive deep learning framework for forecasting the decadal world economic outlook
por: Wang, Tianyi, et al.
Publicado: (2023)

Differential privacy for medical deep learning: methods, tradeoffs, and deployment implications
por: Mohammadi, Marziyeh, et al.
Publicado: (2025)

Exploring the design space of deep-learning-based weather forecasting systems
por: Siddiqui, Shoaib Ahmed, et al.
Publicado: (2024)

Multiplicative update rules for accelerating deep learning training and increasing robustness
por: Kirtas, Manos, et al.
Publicado: (2023)

Why "classic" Transformers are shallow and how to make them go deep
por: Yu, Yueyao, et al.
Publicado: (2023)