Environmental sound recognition is currently an important and valuable field of computer science and robotics, , security or environmental protection. The underlying methodology evolved from primary speech application characteristic methods to more specific approaches, and with the advent of the deep learning paradigm many attempts using these methods arose. The paper reopens the research we have started on the application of the Feed Forward Neural Networks, by exploring several configurations, and introduces the Convolutional Neural Networks in our investigation. The experiments consider three classes of forest specific sounds and meant to detect the chainsaw sounds chainsaw, vehicle, and genuine forest
Research in sound classification and recognition is rapidly advancing in the field of pattern recogn...
With deep great breakthroughs of deep learning in the field of computer vision, the field of audio r...
Cyber-physical systems (CPS) constitute a promising paradigm that could fit variousapplications. Mo...
Environmental sound recognition is currently an important and valuable field of computer science and...
This master thesis deals with the problem of audio-classification of the chainsaw logging sound in n...
Artificial neural networks are computational systems made up of simple processing units that have a ...
The classification of environmental sounds is important for emerging applications such as automatic ...
A convolutional neural network (CNN) training framework is described and implemented. The framework ...
Machine learning has experienced a strong growth in recent years, due to increased dataset sizes and...
Microphones enable computers to receive audio signals as an input, and in turn, enable sound surveil...
Research in sound classification and recognition is rapidly advancing in the field of pattern recogn...
Context. Environmental Sound Recognition, unlike Speech Recognition, is an area that is still in the...
At present, the environment sound recognition system mainly identifies environment sounds with deep ...
Environmental sound identification and recognition aim to detect sound events within an audio clip. ...
Sound event detection (SED) assists in the detainment of intruders. In recent decades, several SED m...
Research in sound classification and recognition is rapidly advancing in the field of pattern recogn...
With deep great breakthroughs of deep learning in the field of computer vision, the field of audio r...
Cyber-physical systems (CPS) constitute a promising paradigm that could fit variousapplications. Mo...
Environmental sound recognition is currently an important and valuable field of computer science and...
This master thesis deals with the problem of audio-classification of the chainsaw logging sound in n...
Artificial neural networks are computational systems made up of simple processing units that have a ...
The classification of environmental sounds is important for emerging applications such as automatic ...
A convolutional neural network (CNN) training framework is described and implemented. The framework ...
Machine learning has experienced a strong growth in recent years, due to increased dataset sizes and...
Microphones enable computers to receive audio signals as an input, and in turn, enable sound surveil...
Research in sound classification and recognition is rapidly advancing in the field of pattern recogn...
Context. Environmental Sound Recognition, unlike Speech Recognition, is an area that is still in the...
At present, the environment sound recognition system mainly identifies environment sounds with deep ...
Environmental sound identification and recognition aim to detect sound events within an audio clip. ...
Sound event detection (SED) assists in the detainment of intruders. In recent decades, several SED m...
Research in sound classification and recognition is rapidly advancing in the field of pattern recogn...
With deep great breakthroughs of deep learning in the field of computer vision, the field of audio r...
Cyber-physical systems (CPS) constitute a promising paradigm that could fit variousapplications. Mo...