AIMC Journal:
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society

Showing 181 to 190 of 191 articles

Nonparametric Bayesian Regression and Classification on Manifolds, With Applications to 3D Cochlear Shapes.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Advanced shape analysis studies such as regression and classification need to be performed on curved manifolds, where often, there is a lack of standard statistical formulations. To overcome these limitations, we introduce a novel machine-learning me...

Multi-Organ Plant Classification Based on Convolutional and Recurrent Neural Networks.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Classification of plants based on a multi-organ approach is very challenging. Although additional data provide more information that might help to disambiguate between species, the variability in shape and appearance in plant organs also raises the d...

Hookworm Detection in Wireless Capsule Endoscopy Images With Deep Learning.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
As one of the most common human helminths, hookworm is a leading cause of maternal and child morbidity, which seriously threatens human health. Recently, wireless capsule endoscopy (WCE) has been applied to automatic hookworm detection. Unfortunately...

Skeleton-Based Human Action Recognition With Global Context-Aware Attention LSTM Networks.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Human action recognition in 3D skeleton sequences has attracted a lot of research attention. Recently, long short-term memory (LSTM) networks have shown promising performance in this task due to their strengths in modeling the dependencies and dynami...

Multi-Task Convolutional Neural Network for Pose-Invariant Face Recognition.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
This paper explores multi-task learning (MTL) for face recognition. First, we propose a multi-task convolutional neural network (CNN) for face recognition, where identity classification is the main task and pose, illumination, and expression (PIE) es...

DeepFix: A Fully Convolutional Neural Network for Predicting Human Eye Fixations.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Understanding and predicting the human visual attention mechanism is an active area of research in the fields of neuroscience and computer vision. In this paper, we propose DeepFix, a fully convolutional neural network, which models the bottom-up mec...

Learning the Personalized Intransitive Preferences of Images.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Most of the previous studies on the user preferences assume that there is a personal transitive preference ranking of the consumable media like images. For example, the transitivity of preferences is one of the most important assumptions in the recom...

Text-Attentional Convolutional Neural Network for Scene Text Detection.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Recent deep learning models have demonstrated strong capabilities for classifying text and non-text components in natural images. They extract a high-level feature globally computed from a whole image component (patch), where the cluttered background...

Cross-View Action Recognition via Transferable Dictionary Learning.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Discriminative appearance features are effective for recognizing actions in a fixed view, but may not generalize well to a new view. In this paper, we present two effective approaches to learn dictionaries for robust action recognition across views. ...

BIT: Biologically Inspired Tracker.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Visual tracking is challenging due to image variations caused by various factors, such as object deformation, scale change, illumination change, and occlusion. Given the superior tracking performance of human visual system (HVS), an ideal design of b...