AIMC Journal:
IEEE transactions on pattern analysis and machine intelligence

Showing 191 to 200 of 300 articles

DeepSPIO: Super Paramagnetic Iron Oxide Particle Quantification Using Deep Learning in Magnetic Resonance Imaging.

IEEE transactions on pattern analysis and machine intelligence Dec 7, 2021
The susceptibility of super paramagnetic iron oxide (SPIO) particles makes them a useful contrast agent for different purposes in MRI. These particles are typically quantified with relaxometry or by measuring the inhomogeneities they produced. These ...
Algorithms Deep Learning Magnetic Resonance Imaging Ferric Compounds
View on PubMed DOI

Learning Meta-Distance for Sequences by Learning a Ground Metric via Virtual Sequence Regression.

IEEE transactions on pattern analysis and machine intelligence Dec 7, 2021
Distance between sequences is structural by nature because it needs to establish the temporal alignments among the temporally correlated vectors in sequences with varying lengths. Generally, distances for sequences heavily depend on the ground metric...
Neural Networks, Computer Algorithms
View on PubMed DOI

A Comprehensive and Modularized Statistical Framework for Gradient Norm Equality in Deep Neural Networks.

IEEE transactions on pattern analysis and machine intelligence Dec 7, 2021
The rapid development of deep neural networks (DNNs) in recent years can be attributed to the various techniques that address gradient explosion and vanishing. In order to understand the principle behind these techniques and develop new methods, plen...
Neural Networks, Computer Algorithms
View on PubMed DOI

Sharing Matters for Generalization in Deep Metric Learning.

IEEE transactions on pattern analysis and machine intelligence Dec 7, 2021
Learning the similarity between images constitutes the foundation for numerous vision tasks. The common paradigm is discriminative metric learning, which seeks an embedding that separates different training classes. However, the main challenge is to ...
Algorithms Deep Learning
View on PubMed DOI

Event-Based Vision: A Survey.

IEEE transactions on pattern analysis and machine intelligence Dec 7, 2021
Event cameras are bio-inspired sensors that differ from conventional frame cameras: Instead of capturing images at a fixed rate, they asynchronously measure per-pixel brightness changes, and output a stream of events that encode the time, location an...
Neural Networks, Computer Algorithms Robotics
View on PubMed DOI

Average Top-k Aggregate Loss for Supervised Learning.

IEEE transactions on pattern analysis and machine intelligence Dec 7, 2021
In this work, we introduce the average top- k ( AT) loss, which is the average over the k largest individual losses over a training data, as a new aggregate loss for supervised learning. We show that the AT loss is a natural generalization of the two...
Algorithms Supervised Machine Learning
View on PubMed DOI

MRA-Net: Improving VQA Via Multi-Modal Relation Attention Network.

IEEE transactions on pattern analysis and machine intelligence Dec 7, 2021
Visual Question Answering (VQA) is a task to answer natural language questions tied to the content of visual images. Most recent VQA approaches usually apply attention mechanism to focus on the relevant visual objects and/or consider the relations be...
Algorithms Natural Language Processing Semantics
View on PubMed DOI

Scalable and Practical Natural Gradient for Large-Scale Deep Learning.

IEEE transactions on pattern analysis and machine intelligence Dec 7, 2021
Large-scale distributed training of deep neural networks results in models with worse generalization performance as a result of the increase in the effective mini-batch size. Previous approaches attempt to address this problem by varying the learning...
Neural Networks, Computer Algorithms Deep Learning
View on PubMed DOI

On Connections Between Regularizations for Improving DNN Robustness.

IEEE transactions on pattern analysis and machine intelligence Nov 3, 2021
This paper analyzes regularization terms proposed recently for improving the adversarial robustness of deep neural networks (DNNs), from a theoretical point of view. Specifically, we study possible connections between several effective methods, inclu...
Neural Networks, Computer Machine Learning Algorithms
View on PubMed DOI

Decoding Brain Representations by Multimodal Learning of Neural Activity and Visual Features.

IEEE transactions on pattern analysis and machine intelligence Oct 1, 2021
This work presents a novel method of exploring human brain-visual representations, with a view towards replicating these processes in machines. The core idea is to learn plausible computational and biological representations by correlating human neur...
Humans Neural Networks, Computer Algorithms Brain Attention Visual Perception
View on PubMed DOI
Popular Topics
Popular Journals