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Found 5 papers, 2 papers with code
Deep Active Audio Feature Learning in Resource-Constrained Environments
The scarcity of labelled data makes training Deep Neural Network (DNN) models in bioacoustic applications challenging.
Pruning vs XNOR-Net: A Comprehensive Study of Deep Learning for Audio Classification on Edge-devices
These technologies must ultimately be brought directly to the edge to fully harness the power of deep learning for the IoT.
Enhancing safety in water transport system based on Internet of Things for developing countries
This paper proposes a model to transform the water transport system into an intelligent system based on IoT.
Environmental Sound Classification on the Edge: A Pipeline for Deep Acoustic Networks on Extremely Resource-Constrained Devices
Significant efforts are being invested to bring state-of-the-art classification and recognition to edge devices with extreme resource constraints (memory, speed, and lack of GPU support).
Ranked #18 on
Audio Classification
on ESC-50
Effect of Hyper-Parameter Optimization on the Deep Learning Model Proposed for Distributed Attack Detection in Internet of Things Environment
This paper studies the effect of various hyper-parameters and their selection for the best performance of the deep learning model proposed in [1] for distributed attack detection in the Internet of Things (IoT).
