The explosive increase and ubiquitous accessibility of visual data on the Web have led to
the prosperity of research activity in image search or retrieval. With the ignorance of visual …

Usage of Unmanned Aerial Vehicles (UAVs) is growing rapidly in a wide range of consumer
applications, as they prove to be both autonomous and flexible in a variety of environments …

In late fusion, each modality is processed in a separate unimodal Convolutional Neural
Network (CNN) stream and the scores of each modality are fused at the end. Due to its …

The recent years have witnessed a surge of interests in data analytics with patient Electronic
Health Records (EHR). Data-driven healthcare, which aims at effective utilization of big …

Multi-view clustering, which seeks a partition of the data inmultiple views that often provide
complementary information to eachother, has received considerable attention in recent …

Classifying videos according to content semantics is an important problem with a wide range
of applications. In this paper, we propose a hybrid deep learning framework for video …

In this paper, we study the challenging problem of categorizing videos according to high-
level semantics such as the existence of a particular human action or a complex event …

We present a method for gesture detection and localisation based on multi-scale and multi-
modal deep learning. Each visual modality captures spatial information at a particular spatial …

The employed dictionary plays an important role in sparse representation or sparse coding
based image reconstruction and classification, while learning dictionaries from the training …

This paper studies deep network architectures to address the problem of video classification.
A multi-stream framework is proposed to fully utilize the rich multimodal information in …