AI Medical Compendium Journal:
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society

Showing 141 to 150 of 191 articles

Sample Fusion Network: An End-to-End Data Augmentation Network for Skeleton-Based Human Action Recognition.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Data augmentation is a widely used technique for enhancing the generalization ability of deep neural networks for skeleton-based human action recognition (HAR) tasks. Most existing data augmentation methods generate new samples by means of handcrafte...

Deep Attention Network for Egocentric Action Recognition.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Recognizing a camera wearer's actions from videos captured by an egocentric camera is a challenging task. In this paper, we employ a two-stream deep neural network composed of an appearance-based stream and a motion-based stream to recognize egocentr...

Predicting Human Saccadic Scanpaths Based on Iterative Representation Learning.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Visual attention is a dynamic process of scene exploration and information acquisition. However, existing research on attention modeling has concentrated on estimating static salient locations. In contrast, dynamic attributes presented by saccade hav...

Sparse Representation Over Learned Dictionaries on the Riemannian Manifold for Automated Grading of Nuclear Pleomorphism in Breast Cancer.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Breast cancer is found to be the most pervasive type of cancer among women. Computer aided detection and diagnosis of cancer at the initial stages can increase the chances of recovery and thus reduce the mortality rate through timely prognosis and ad...

Learning to Segment Object Candidates via Recursive Neural Networks.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
To avoid the exhaustive search over locations and scales, current state-of-the-art object detection systems usually involve a crucial component generating a batch of candidate object proposals from images. In this paper, we present a simple yet effec...

Contour-Seed Pairs Learning-Based Framework for Simultaneously Detecting and Segmenting Various Overlapping Cells/Nuclei in Microscopy Images.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
In this paper, we propose a novel contour-seed pairs learning-based framework for robust and automated cell/nucleus segmentation. Automated granular object segmentation in microscopy images has significant clinical importance for pathology grading of...

Fight Recognition in video using Hough Forests and 2D Convolutional Neural Network.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
While action recognition has become an important line of research in computer vision, the recognition of particular events such as aggressive behaviors, or fights, has been relatively less studied. These tasks may be extremely useful in several video...

3D Randomized Connection Network with Graph-based Label Inference.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
In this paper, a novel 3D deep learning network is proposed for brain MR image segmentation with randomized connection, which can decrease the dependency between layers and increase the network capacity. The convolutional LSTM and 3D convolution are ...

Deep Spatiality: Unsupervised Learning of Spatially-Enhanced Global and Local 3D Features by Deep Neural Network with Coupled Softmax.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
The discriminability of Bag-of-Words representations can be increased via encoding the spatial relationship among virtual words on 3D shapes. However, this encoding task involves several issues, including arbitrary mesh resolutions, irregular vertex ...

Deep Visual Attention Prediction.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
In this paper, we aim to predict human eye fixation with view-free scenes based on an end-to-end deep learning architecture. Although convolutional neural networks (CNNs) have made substantial improvement on human attention prediction, it is still ne...