Low-Complexity Acoustic Scene Classification In Dcase 2022 Challenge
Objective
The objective of the "Low-Complexity Acoustic Scene Classification in DCASE 2022 Challenge" is to develop and implement efficient and effective algorithms for acoustic scene classification (ASC) that are optimized for low-complexity computational requirements.
Abstract
The "Low-Complexity Acoustic Scene Classification in DCASE 2022 Challenge" focuses on the development and deployment of streamlined algorithms tailored to acoustic scene classification (ASC) tasks, with a specific emphasis on minimizing computational resource demands. In this challenge, participants aim to create efficient and highly effective ASC solutions, addressing the growing need for real-time audio analysis in various applications, including smart cities, surveillance, and augmented reality systems. By optimizing computational requirements, these algorithms seek to strike a balance between accuracy and efficiency, enabling ASC systems to function seamlessly on resource-constrained devices while maintaining robust performance. The challenge represents a critical step in advancing ASC technology, facilitating the integration of intelligent audio analysis into a wide range of low-power, edge computing devices and enhancing their capabilities to accurately identify and classify acoustic scenes in real-world environments.
Keywords: ASC technology, low-power, edge computing devices, DCASE 2022.
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.
Specifications
Software: Matlab 2020a or above
Hardware:
Operating Systems:
- Windows 10
- Windows 7 Service Pack 1
- Windows Server 2019
- Windows Server 2016
Processors:
Minimum: Any Intel or AMD x86-64 processor
Recommended: Any Intel or AMD x86-64 processor with four logical cores and AVX2 instruction set support
Disk:
Minimum: 2.9 GB of HDD space for MATLAB only, 5-8 GB for a typical installation
Recommended: An SSD is recommended A full installation of all MathWorks products may take up to 29 GB of disk space
RAM:
Minimum: 4 GB
Recommended: 8 GB
Learning Outcomes
· Introduction to Matlab
· What is EISPACK & LINPACK
· How to start with MATLAB
· About Matlab language
· Matlab coding skills
· About tools & libraries
· Application Program Interface in Matlab
· About Matlab desktop
· How to use Matlab editor to create M-Files
· Features of Matlab
· Basics on Matlab
· What is an Image/pixel?
· About image formats
· Introduction to Image Processing
· How digital image is formed
· Importing the image via image acquisition tools
· Analyzing and manipulation of image.
· Phases of image processing:
o Acquisition
o Image enhancement
o Image restoration
o Color image processing
o Image compression
o Morphological processing
o Segmentation etc.,
· How to extend our work to another real time applications
· Project development Skills
o Problem analyzing skills
o Problem solving skills
o Creativity and imaginary skills
o Programming skills
o Deployment
o Testing skills
o Debugging skills
o Project presentation skills
o Thesis writing skills
Paper Publishing
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