Intrusion detection in computer networks is of great importance because of its effects on the
different communication and security domains. The detection of network intrusion is a …

Early detection of Alzheimer's disease (AD) is vital for adequate control. Machine learning
techniques have gained much attraction due to their efficiency in predicting AD using …

Multi-label classification is the task of inferring the set of unseen instances using the
knowledge obtained through the analysis of a set of training examples with known label …

The term 'IoT'is a trendy word in current era due to its usage in day to day live of human
beings. Its applications are widespread across many areas such as home, agriculture …

Spirits are a prime target for fraudulent activity. Particular brands, production processes, and
other factors such as age can carry high value, and leave space for mimicry. Further, the …

In this thesis, we study methods to create ensembles of deep neural networks. Ensembles of
deep neural networks are sets of deep networks whose outputs are fused together to obtain …

Intrusion detection in computer networks is of great importance because of its effects on the
different communication and security domains. The detection of network intrusion is a …

The concept of Multi-component shapes is motivated by researchers in image classification
and computer vision applications. In this paper, we have introduced several descriptors that …

Purpose: This presented work demonstrates a mixture of the MLPNN/HMM model for
operational Hindi writing recognition. The planned structure is proposed on behalf of HMMs …

In the context of machine learning, classification is the task of identifying which class an
instance belongs according to the knowledge obtained through a training set, that is, a set of …