Environmental Noise Classification Using Convolutional Neural Networks with Input Transform for Hearing Aids
نویسندگان
چکیده
منابع مشابه
Image Classification using Convolutional Neural Networks
The specific paper I’ve chosen is titled “ImageNet Classification with Deep Convolutional Neural Networks” [1]. ImageNet is an annual competition in image recognition where researchers in the field pit their models against each other to achieve the highest classification accuracy on the same set of images. The model put forward in this paper, named AlexNet from it’s main author, beat the second...
متن کاملAcoustic Event Classification Using Convolutional Neural Networks
Acoustic scene classification (ASC) aims to distinguish between different acoustic environments and is a technology which can be used by smart devices for contextualization and personalization. Standard algorithms exploit hand-crafted features which are unlikely to offer the best potential for reliable classification. This paper reports the first application of convolutional neural networks (CN...
متن کاملMedical Text Classification using Convolutional Neural Networks
We present an approach to automatically classify clinical text at a sentence level. We are using deep convolutional neural networks to represent complex features. We train the network on a dataset providing a broad categorization of health information. Through a detailed evaluation, we demonstrate that our method outperforms several approaches widely used in natural language processing tasks by...
متن کاملSpectral classification using convolutional neural networks
There is a great need for accurate and autonomous spectral classification methods in astrophysics. This thesis is about training a convolutional neural network (ConvNet) to recognize an object class (quasar, star or galaxy) from one-dimension spectra only. Author developed several scripts and C programs for datasets preparation, preprocessing and postprocessing of the data. EBLearn library (dev...
متن کاملAcoustic Scene Classification Using Convolutional Neural Networks
Acoustic scene classification (ASC) aims to distinguish between different acoustic environments and is a technology which can be used by smart devices for contextualization and personalization. Standard algorithms exploit hand-crafted features which are unlikely to offer the best potential for reliable classification. This paper reports the first application of convolutional neural networks (CN...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Environmental Research and Public Health
سال: 2020
ISSN: 1660-4601
DOI: 10.3390/ijerph17072270