Adopting the YOLOv4 architecture for low-latency multispectral pedestrian detection in autonomous driving

K Roszyk, MR Nowicki, P Skrzypczyński - Sensors, 2022 - mdpi.com
Detecting pedestrians in autonomous driving is a safety-critical task, and the decision to
avoid aa person has to be made with minimal latency. Multispectral approaches that …

Two decades of local binary patterns: A survey

M Pietikäinen, G Zhao - Advances in independent component analysis and …, 2015 - Elsevier
Texture is an important characteristic for many types of images. In recent years, very
discriminative and computationally efficient local texture descriptors based on local binary …

A method of underwater acoustic signal classification based on deep neural network

Z Wei, Y Ju, M Song - 2018 5th International Conference on …, 2018 - ieeexplore.ieee.org
As an important precondition for underwater acoustic signal analysis and underwater target
detection & identification, classification of underwater acoustic sensor signal (especially in …

Active contour-based detection of estuarine dolphin whistles in spectrogram images

OM Serra, FPR Martins, LR Padovese - Ecological Informatics, 2020 - Elsevier
An algorithm for detecting tonal vocalizations from estuarine dolphin (Sotalia guianensis)
specimens without interference of a human operator was developed. The raw audio data …

Gated weighted normative feature fusion for multispectral object detection

X Wu, X Jiang, L Dong - The Visual Computer, 2024 - Springer
Multispectral image pairs can provide independent and complementary information to more
comprehensively describe detection targets, thereby improving the robustness and reliability …

A permanent automated real-time passive acoustic monitoring system for bottlenose dolphin conservation in the Mediterranean Sea

M Brunoldi, G Bozzini, A Casale, P Corvisiero… - PloS one, 2016 - journals.plos.org
Within the framework of the EU Life+ project named LIFE09 NAT/IT/000190 ARION, a
permanent automated real-time passive acoustic monitoring system for the improvement of …

Classification of EMI discharge sources using time–frequency features and multi-class support vector machine

I Mitiche, G Morison, A Nesbitt… - Electric Power Systems …, 2018 - Elsevier
This paper introduces the first application of feature extraction and machine learning to
electromagnetic interference (EMI) signals for discharge sources classification in high …

Underwater acoustic target recognition with fusion feature

P Qi, J Sun, Y Long, L Zhang, Tianye - … 8–12, 2021, Proceedings, Part I 28, 2021 - Springer
For the underwater acoustic targets recognition, it is a challenging task to provide good
classification accuracy for underwater acoustic target using radiated acoustic signals …

Two-stage detection of north Atlantic right whale upcalls using local binary patterns and machine learning algorithms

M Esfahanian, N Erdol, E Gerstein, H Zhuang - Applied Acoustics, 2017 - Elsevier
In this paper, we investigate the effectiveness of two-stage classification strategies in
detecting north Atlantic right whale upcalls. Time-frequency measurements of data from …

Application of image processing techniques for frog call classification

J **e, M Towsey, J Zhang, X Dong… - 2015 IEEE International …, 2015 - ieeexplore.ieee.org
Frogs have received increasing attention due to their effectiveness for indicating the
environment change. Therefore, it is important to monitor and assess frogs. With the …