|
|
|
|
|
Mondher Bouazizi, Chuheng Zheng, Siyuan Yang and Tomoaki Ohtsuki
A growing focus among scientists has been on researching the techniques of automatic detection of dementia that can be applied to the speech samples of individuals with dementia. Leveraging the rapid advancements in Deep Learning (DL) and Natural Languag...
ver más
|
|
|
|
|
|
|
|
|
Peranut Nimitsurachat and Peter Washington
Emotion recognition models using audio input data can enable the development of interactive systems with applications in mental healthcare, marketing, gaming, and social media analysis. While the field of affective computing using audio data is rich, a m...
ver más
|
|
|
|
|
|
|
|
|
Ru Ye, Hongyan Xing and Xing Zhou
Addressing the limitations of manually extracting features from small maritime target signals, this paper explores Markov transition fields and convolutional neural networks, proposing a detection method for small targets based on an improved Markov tran...
ver más
|
|
|
|
|
|
|
|
|
Tapan Chatterjee, Usha Rani Gogoi, Animesh Samanta, Ayan Chatterjee, Mritunjay Kumar Singh and Srinivas Pasupuleti
Groundwater quality is one of the major concerns. Quality of the groundwater directly impacts human health, growth of plants and vegetables. Due to the severe impacts of inadequate water quality, it is imperative to find a swift and economical solution. ...
ver más
|
|
|
|
|
|
|
|
|
Youngki Park and Youhyun Shin
In this paper, we introduce an efficient approach to multi-label image classification that is particularly suited for scenarios requiring rapid adaptation to new classes with minimal training data. Unlike conventional methods that rely solely on neural n...
ver más
|
|
|
|