Long short-term memory (LSTM) has transformed both machine learning and
neurocomputing fields. According to several online sources, this model has improved …

Deep Learning has implemented a wide range of applications and has become increasingly
popular in recent years. The goal of multimodal deep learning (MMDL) is to create models …

Pedestrian trajectory prediction is an extremely challenging problem because of the
crowdedness and clutter of the scenes. Previous deep learning LSTM-based approaches …

Weather Recognition plays an important role in our daily lives and many computer vision
applications. However, recognizing the weather conditions from a single image remains …

Pedestrian path prediction is a very challenging problem because scenes are often crowded
or contain obstacles. Existing state-of-the-art long short-term memory (LSTM)-based …

We propose a novel attention framework called attentive linear transformation (ALT) for
automatic generation of image captions. Instead of learning the spatial or channel-wise …

Geometric deep learning has sparked a rising interest in computer graphics to perform
shape understanding tasks, such as shape classification and semantic segmentation. When …

Remote sensing data is growing enormously by virtue of the advancements in satellite and
drone technology. Generating description of these remote sensing images have gained …

Deep learning (DL) is a kind of sophisticated data analysis and image processing
technology, with good results and great potential. DL has been applied to many different …

Visual saliency and semantic saliency are important in image captioning. However, a single-
phase image captioning model benefits little from limited saliency information without a …