The recognition and map** of landslide (RML) is an important task in hazard and risk
research and can provide a scientific basis for the prevention and control of landslide …

White blood cells (leukocytes) are a very important component of the blood that forms the
immune system, which is responsible for fighting foreign elements. The five types of white …

Recent deep neural networks (DNNs) with several layers of feature representations rely on
some form of skip connections to simultaneously circumnavigate optimization problems and …

Electrical impedance tomography (EIT) is an effective technique for real-time monitoring,
visualization, and analysis of industrial process in a noninvasive manner. However, due to …

State-of-the-art deep neural networks (DNNs) typically consist of several layers of features
representations, and especially rely on skip connections to avoid the difficulty of model …

State-of-the-art Deep Neural Networks (DNNs) are typically too cumbersome to be
practically useful in portable electronic devices. As such, several works pursue model …

We propose the training of very deep neural networks (DNNs) without shortcut connections
known as PlainNets. Training such networks is a notoriously hard problem due to:(1) the …

Recurrent neural networks (RNNs) are well-suited for sequential data processing, which
have been widely used in natural language processing, speech recognition, and other …

Training the classical-vanilla deep neural networks (DNNs) with several layers is
problematic due to optimization problems. Interestingly, skip connections of various forms …

Very deep networks are successful in various tasks with reported results surpassing human
performance. However, training such very deep networks is not trivial. Typically, the …