International journal of neural systems
Dec 4, 2014
In this paper, we present general methods that can be used to explore the information processing potential of a medium composed of oscillating (self-exciting) droplets. Networks of Belousov-Zhabotinsky (BZ) droplets seem especially interesting as che...
This paper presents a novel algorithm for terrain type classification based on monocular video captured from the viewpoint of human locomotion. A texture-based algorithm is developed to classify the path ahead into multiple groups that can be used to...
BACKGROUND: Insect behavior is often monitored by human observers and measured in the form of binary responses. This procedure is time costly and does not allow a fine graded measurement of behavioral performance in individual animals. To overcome th...
Recognizing human actions in 3-D video sequences is an important open problem that is currently at the heart of many research domains including surveillance, natural interfaces and rehabilitation. However, the design and development of models for act...
This paper proposes a unified framework for multiple/single-view human action recognition. First, we propose the hierarchical partwise bag-of-words representation which encodes both local and global visual saliency based on the body structure cue. Th...
IEEE transactions on neural networks and learning systems
Jul 14, 2014
Monocular multiple-object tracking is a fundamental yet under-addressed computer vision problem. In this paper, we propose a novel learning framework for tracking multiple objects by detection. First, instead of heuristically defining a tracking algo...
Abnormal behavior detection in crowd scenes is continuously a challenge in the field of computer vision. For tackling this problem, this paper starts from a novel structure modeling of crowd behavior. We first propose an informative structural contex...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jun 19, 2014
In orthopedic and trauma surgery, AR technology can support surgeons in the challenging task of understanding the spatial relationships between the anatomy, the implants and their tools. In this context, we propose a novel augmented visualization of ...
The actions of animals provide a window into how their minds work. Recent advances in deep learning are providing powerful approaches to recognize patterns of animal movement from video recordings using markerless pose estimation models. Current meth...
BACKGROUND/AIMS: Artificial intelligence (AI) in Ophthalmology has yet to be applied to real-time cataract surgery. This work explores a new AI tool, developed for phacoemulsification, and evaluates its potential uses.First, our study aimed to demons...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.