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Health Monitoring of Industrial machines using Scene-Aware Threshold Selection
In classification, our hypothesis is that the reconstruction error computed for an abnormal machine is larger than that of the a normal machine, since only normal machine sounds are being used to train the autoencoder.
Multiscale CNN based Deep Metric Learning for Bioacoustic Classification: Overcoming Training Data Scarcity Using Dynamic Triplet Loss
Experimental results also confirm the superiority of the triplet loss over the cross-entropy loss in low training data conditions
Directional Embedding Based Semi-supervised Framework For Bird Vocalization Segmentation
The proposed framework utilizes a reference directional model for obtaining a feature representation called directional embeddings (DE).
Conv-codes: Audio Hashing For Bird Species Classification
In this work, we propose a supervised, convex representation based audio hashing framework for bird species classification.
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