Monitoring of human and social activities is becoming increasingly pervasive in our living
environment for public security and safety applications. The recognition of suspicious events …

Lung sounds convey relevant information related to pulmonary disorders, and to evaluate
patients with pulmonary conditions, the physician or the doctor uses the traditional …

The conventional audio feature extraction methods employed in the audio analysis are
categorized into time-domain and frequency-domain. Recently, a new audio feature …

This paper presents a new approach to classify environmental sounds using a texture
feature local binary pattern (LBP) and audio features collaboration. To our knowledge, this is …

Radar gait recognition is robust to light variations and less infringement on privacy. Previous
studies often utilize either spectrograms or cadence velocity diagrams. While the former …

In real life, acoustic scenes and audio events are naturally correlated. Humans instinctively
rely on fine-grained audio events as well as the overall sound characteristics to distinguish …

Whistle contour extraction aims to derive animal whistles from time-frequency spectrograms
as polylines. For toothed whales, whistle extraction results can serve as the basis for …

Deep learning has been successfully applied to learn local feature descriptors in recent
years. However, most of existing methods are supervised methods relying on a large …

Automatic speech/music classification is an important tool in multimedia content analysis
and retrieval which efficiently categorizes input audio and store it into relevant classes. This …

Classification of complex acoustic scenes under real time scenarios is an active domain
which has engaged several researchers lately form the machine learning community. A …