3 papers
eess.AS2019
Multiscale CNN based Deep Metric Learning for Bioacoustic Classification: Overcoming Training Data Scarcity Using Dynamic Triplet Loss
Anshul Thakur, Daksh Thapar, Padmanabhan Rajan +1
This paper proposes multiscale convolutional neural network (CNN)-based deep metric learning for bioacoustic classification, under low training data conditions. The proposed CNN is…
eess.AS2019
Directional Embedding Based Semi-supervised Framework For Bird Vocalization Segmentation
Anshul Thakur, Padmanabhan Rajan
This paper proposes a data-efficient, semi-supervised, two-pass framework for segmenting bird vocalizations. The framework utilizes a binary classification model to categorize fram…
eess.AS2019
Conv-codes: Audio Hashing For Bird Species Classification
Anshul Thakur, Pulkit Sharma, Vinayak Abrol +1
In this work, we propose a supervised, convex representation based audio hashing framework for bird species classification. The proposed framework utilizes archetypal analysis, a m…