Toward deep neural networks: Mirror extreme learning machines for pattern classification
نویسندگان
چکیده
منابع مشابه
Learning deep representations via extreme learning machines
Extreme learning machine (ELM) as an emerging technology has achieved exceptional performance in large-scale settings, and is well suited to binary and multi-class classification, as well as regression tasks. However, existing ELM and its variants predominantly employ single hidden layer feedforward networks, leaving the popular and potentially powerful stacked generalization principle unexploi...
متن کاملComparing Error Minimized Extreme Learning Machines and Support Vector Sequential Feedforward Neural Networks for Classification Problems
Recently, error minimized extreme learning machines (EM-ELMs) have been proposed as a simple and efficient approach to build single-hidden-layer feedforward networks (SLFNs) sequentially. They add random hidden nodes one by one (or group by group) and update the output weights incrementally to minimize the sum-of-squares error in the training set. Other very similar methods that also construct ...
متن کاملExtreme learning machines for Internet traffic classification
Network packet transport services (namely the Internet) are subject to significant security issues. This paper aims to apply Machine Learning methods based on Neural Networks (Extreme Learning Machines or ELM) to analyze the Internet traffic in order to detect specific malicious activities. This is performed by classifying traffic for a key service run over the internet: the Domain Name System ...
متن کاملMetagenomic Taxonomic Classification Using Extreme Learning Machines
Next-generation sequencing technologies have allowed researchers to determine the collective genomes of microbial communities co-existing within diverse ecological environments. Varying species abundance, length and complexities within different communities, coupled with discovery of new species makes the problem of taxonomic assignment to short DNA sequence reads extremely challenging. We have...
متن کاملA New Method for Detecting Ships in Low Size and Low Contrast Marine Images: Using Deep Stacked Extreme Learning Machines
Detecting ships in marine images is an essential problem in maritime surveillance systems. Although several types of deep neural networks have almost ubiquitously used for this purpose, but the performance of such networks greatly drops when they are exposed to low size and low contrast images which have been captured by passive monitoring systems. On the other hand factors such as sea waves, c...
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: Filomat
سال: 2020
ISSN: 0354-5180,2406-0933
DOI: 10.2298/fil2015985l