|
|
|
|
|
Zhenwen He, Chi Zhang and Yunhui Cheng
Time series data typically exhibit high dimensionality and complexity, necessitating the use of specific approximation methods to perform computations on the data. The currently employed compression methods suffer from varying degrees of feature loss, le...
ver más
|
|
|
|
|
|
|
|
|
Tulsi Patel, Mark W. Jones and Thomas Redfern
We present a novel approach to providing greater insight into the characteristics of an unlabelled dataset, increasing the efficiency with which labelled datasets can be created. We leverage dimension-reduction techniques in combination with autoencoders...
ver más
|
|
|
|
|
|
|
|
|
Wenxia Lu, Xueyong Tian, Yongguang Ma, Yinyan Guan, Libo Liu and Liwei Shi
Sewage treatment plants face significant problems as a result of the annual growth in urban sewage discharge. Substandard sewage discharge can also be caused by rising sewage treatment expenses and unpredictable procedures. The most widely used sewage tr...
ver más
|
|
|
|
|
|
|
|
|
Cuiran Li, Yongjie Lu, Jianli Xie and Zepeng Zhang
This paper proposes an intelligent reflecting surface (IRS)-assisted energy efficiency optimization algorithm to address the problem of energy efficiency (EE) degradation in high-speed rail communication systems caused by line-of-sight link blockages bet...
ver más
|
|
|
|
|
|
|
|
|
Ting Guo, Nurmemet Yolwas and Wushour Slamu
Recently, the performance of end-to-end speech recognition has been further improved based on the proposed Conformer framework, which has also been widely used in the field of speech recognition. However, the Conformer model is mostly applied to very wid...
ver más
|
|
|
|