In humans, Attention is a core property of all perceptual and cognitive operations. Given our
limited ability to process competing sources, attention mechanisms select, modulate, and …

State-of-the-art methods in the image-to-image translation are capable of learning a
mapping from a source domain to a target domain with unpaired image data. Though the …

The state-of-the-art approaches in Generative Adversarial Networks (GANs) are able to
learn a mapping function from one image domain to another with unpaired image data …

With the development of deep learning, supervised feature learning methods have achieved
prominent performance in the field of aerial scene classification. However, supervised …

Purpose To suggest an attention-aware, cycle-consistent generative adversarial network (A-
CycleGAN) enhanced with variational autoencoding (VAE) as a superior alternative to …

Recently, deep learning methods, in particular, convolutional neural networks (CNNs), have
made a massive breakthrough in computer vision. And a big amount of annotated data is the …

Unsupervised image-to-image translation has received considerable attention due to the
recent remarkable advancements in generative adversarial networks (GANs). In image-to …

To apply powerful deep-learning-based algorithms for object detection and classification in
infrared videos, it is necessary to have more training data in order to build high-performance …

Recently deep learning methods, in particular, convolutional neural networks (CNNs), have
led to a massive breakthrough in the range of computer vision. Also, the large-scale …

As the fundamental research of affective computing, speech emotion recognition (SER) has
gained a lot of attention. Unlike with common deep learning tasks, SER was restricted by the …