Ilyass Moummad

scl_icbhi2017. PyTorch implementation of our work: Pretraining Respiratory Sound Representations using Metadata and Contrastive Learning (WASPAA 2023)

ProtoCLR. Pytorch implementation of our work "Domain-Invariant Representation Learning of Bird Sounds" (ICASSP 2026)

Mix2. Mix2 (Mixture of Mixups), a framework to handle multi-label and class imbalance. Experiments on AnuraSet, a dataset of anuran sounds. (EUSIPCO 2024)

dcase23_task5_scl. System that ranked 2nd in DCASE 2023 Challenge Task 5: Few-shot Bioacoustic Event Detection

ssl4birdsounds. Self-supervised representation learning for bird sounds (ICASSPW SASB 2024)

RCL_FS_BSED. Regularized Contrastive Learning for Few-shot Bioacoustic Sound Event Detection (ICASSP 2024)

cross-view-code-alignment. Pytorch implementation of the "Image Hashing via Cross-View Code Alignment in the Age of Foundation Models", CVPRW 2026 ECV

hashing-baseline. Pytorch implementation of the paper "Hashing-Baseline: Rethinking Hashing in the Age of Pretrained Models", ICASSP 2026

sslplant. [ICPR CVBMC 2026] SimDINOv2 for Self-Supervised Representation Learning of Plant Images

BioAcousticInference. BioAcoustic Inference, an easy tool to annotate your audio files of animal sounds using very few manual annotation as little as one.

dcase-few-shot-bioacoustic. Python

CLRW. Self-supervised contrastive learning objective using random walk laplacian (GSP Workshop 2023)

distillplant. [ICPR GREEN-PR 2026] Pytorch Code for Knowledge Distillation in Plant Recognition Tasks.