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

Showing 161 to 170 of 191 articles

Manifold Regularized Experimental Design for Active Learning.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Various machine learning and data mining tasks in classification require abundant data samples to be labeled for training. Conventional active learning methods aim at labeling the most informative samples for alleviating the labor of the user. Many p...

A Non-Greedy Algorithm for L1-Norm LDA.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Recently, L1-norm-based discriminant subspace learning has attracted much more attention in dimensionality reduction and machine learning. However, most existing approaches solve the column vectors of the optimal projection matrix one by one with gre...

A Feature Learning and Object Recognition Framework for Underwater Fish Images.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Live fish recognition is one of the most crucial elements of fisheries survey applications where the vast amount of data is rapidly acquired. Different from general scenarios, challenges to underwater image recognition are posted by poor image qualit...

Constrained Metric Learning by Permutation Inducing Isometries.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
The choice of metric critically affects the performance of classification and clustering algorithms. Metric learning algorithms attempt to improve performance, by learning a more appropriate metric. Unfortunately, most of the current algorithms learn...

Detect2Rank: Combining Object Detectors Using Learning to Rank.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Object detection is an important research area in the field of computer vision. Many detection algorithms have been proposed. However, each object detector relies on specific assumptions of the object appearance and imaging conditions. As a consequen...

Close Human Interaction Recognition Using Patch-Aware Models.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
This paper addresses the problem of recognizing human interactions with close physical contact from videos. Due to ambiguities in feature-to-person assignments and frequent occlusions in close interactions, it is difficult to accurately extract the i...

Multimodal Task-Driven Dictionary Learning for Image Classification.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Dictionary learning algorithms have been successfully used for both reconstructive and discriminative tasks, where an input signal is represented with a sparse linear combination of dictionary atoms. While these methods are mostly developed for singl...

Multimodal Deep Autoencoder for Human Pose Recovery.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Video-based human pose recovery is usually conducted by retrieving relevant poses using image features. In the retrieving process, the mapping between 2D images and 3D poses is assumed to be linear in most of the traditional methods. However, their r...

Kernelized Saliency-Based Person Re-Identification Through Multiple Metric Learning.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Person re-identification in a non-overlapping multi-camera scenario is an open and interesting challenge. While the task can hardly be completed by machines, we, as humans, are inherently able to sample those relevant persons' details that allow us t...

Cost-Sensitive Local Binary Feature Learning for Facial Age Estimation.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
In this paper, we propose a cost-sensitive local binary feature learning (CS-LBFL) method for facial age estimation. Unlike the conventional facial age estimation methods that employ hand-crafted descriptors or holistically learned descriptors for fe...