6 papers
Parameter-efficient Dual-encoder Architecture with Differentiable Choquet Integral Fusion for Underwater Acoustic Classification
Amirmohammad Mohammadi, Joshua Peeples, Alexandra Van Dine
Underwater acoustic classification has a wide array of oceanic applications, but faces challenges due to an increasingly complex acoustic environment. Waveform and spectrogram repr…
Histogram-based Parameter-efficient Tuning for Passive and Active Sonar Classification
Amirmohammad Mohammadi, Davelle Carreiro, Alexandra Van Dine +1
Parameter-efficient transfer learning (PETL) methods adapt large artificial neural networks to downstream tasks without fine-tuning the entire model. However, existing additive met…
Structural and Statistical Audio Texture Knowledge Distillation for Acoustic Classification
Jarin Ritu, Amirmohammad Mohammadi, Davelle Carreiro +2
While knowledge distillation has shown success in various audio tasks, its application to environmental sound classification often overlooks essential low-level audio texture featu…
Neighborhood Feature Pooling for Remote Sensing Image Classification
Fahimeh Orvati Nia, Amirmohammad Mohammadi, Salim Al Kharsa +3
In this work, we introduce Neighborhood Feature Pooling (NFP), a novel pooling layer designed to enhance texture-aware representation learning for remote sensing image classificati…
Investigation of Time-Frequency Feature Combinations with Histogram Layer Time Delay Neural Networks
Amirmohammad Mohammadi, Iren'e Masabarakiza, Ethan Barnes +3
While deep learning has reduced the prevalence of manual feature extraction, transformation of data via feature engineering remains essential for improving model performance, parti…
Cross-Domain Knowledge Transfer for Underwater Acoustic Classification Using Pre-trained Models
Amirmohammad Mohammadi, Tejashri Kelhe, Davelle Carreiro +2
Transfer learning is commonly employed to leverage large, pre-trained models and perform fine-tuning for downstream tasks. The most prevalent pre-trained models are initially train…