Human trajectory Prediction (HTP) in complex social environments plays a crucial and fundamental role artificial intelligence systems. Conventional methods make use of both history behaviors interactions to forecast future trajectories. However, we demonstrate that the environment is confounder misleads model learn spurious correlations between To end this, first formulate environment, variable...

Sound source separation is the of targeted sounds from a noisy environment, which plays an important role in signal processing and has been studied extensively. However, most these researches only extract audio information for processing, ignoring visual information, resulting waste feature information. In addition, some researchers have fused extracted features but not noticed weights differen...

Automatic image caption prediction is a challenging task in natural language processing. Most of the researchers have used convolutional neural network as an encoder and decoder. However, accurate requires model to understand semantic relationship that exists between various objects present image. The attention mechanism performs linear combination decoder states. It emphasizes information with...

Facial attribute editing has mainly two objectives: 1) translating image from a source domain to target one, and 2) only changing the facial regions related preserving attribute-excluding details. In this work, we propose multi-attention U-Net-based generative adversarial network (MU-GAN). First, replace classic convolutional encoder-decoder with symmetric U-Net-like structure in generator, the...

The understanding of long-range pixel–pixel dependencies plays a vital role in image segmentation. use CNN plus an attention mechanism still has room for improvement, since existing transformer-based architectures require many thousands annotated training samples to model spatial dependencies. This paper presents smooth branch (SAB), novel architecture that simplifies the biomedical segmentatio...

Spatiotemporal fusion is an effective and cost-effective method to obtain both high temporal resolution spatial images. However, existing methods do not sufficiently extract the deeper features of image, resulting in fused images which recover good topographic detail poor quality. In order higher quality spatiotemporal images, a novel based on deep learning proposed this paper. The combines att...

Background: Attention impairments are the hallmark feature of subclinical depression. The present study used Navon task to compare the allocation of attention to the local and global stimuli in depressed and nondepressed participants. Method: The primary sample included 186 female high school students from Shiraz city who were selected using cluster sampl...

BACKGROUND While stimulant therapy has been shown to be effective in the treatment of attention-deficit/hyperactivity disorder (ADHD), there is less information concerning differences between alternative stimulant medications. The purpose of this study is to examine how different formulations of methylphenidate (MPH) affect treatment patterns and hospitalizations. METHODS From a large claims ...

The understanding of the control of eye movements has greatly benefited from the analysis of mathematical models. Currently most comprehensive models include sequential shifts of visual attention. Here we propose an alternative model of eye movement control, which includes three new principles: spatially distributed lexical processing, a separation of saccade timing from saccade target selectio...

BACKGROUND To validate the association between country-of-birth and disparities in the stimulant use for ADHD among individuals in Western Australia. METHODS Using linked data, a population-based retrospective cohort of individuals admitted to hospital before age 25 years was followed through to identify having stimulants for ADHD in 2003-2007. Multivariate logistic and linear regressions wer...