AIMC Topic: Algorithms

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Spherical DNNs and Their Applications in 360 Images and Videos.

IEEE transactions on pattern analysis and machine intelligence
Spherical images or videos, as typical non-euclidean data, are usually stored in the form of 2D panoramas obtained through an equirectangular projection, which is neither equal area nor conformal. The distortion caused by the projection limits the pe...

Towards End-to-End Text Spotting in Natural Scenes.

IEEE transactions on pattern analysis and machine intelligence
Text spotting in natural scene images is of great importance for many image understanding tasks. It includes two sub-tasks: text detection and recognition. In this work, we propose a unified network that simultaneously localizes and recognizes text w...

ProtTrans: Toward Understanding the Language of Life Through Self-Supervised Learning.

IEEE transactions on pattern analysis and machine intelligence
Computational biology and bioinformatics provide vast data gold-mines from protein sequences, ideal for Language Models (LMs) taken from Natural Language Processing (NLP). These LMs reach for new prediction frontiers at low inference costs. Here, we ...

Wasserstein Adversarial Regularization for Learning With Label Noise.

IEEE transactions on pattern analysis and machine intelligence
Noisy labels often occur in vision datasets, especially when they are obtained from crowdsourcing or Web scraping. We propose a new regularization method, which enables learning robust classifiers in presence of noisy data. To achieve this goal, we p...

Deep Feature Space: A Geometrical Perspective.

IEEE transactions on pattern analysis and machine intelligence
One of the most prominent attributes of Neural Networks (NNs) constitutes their capability of learning to extract robust and descriptive features from high dimensional data, like images. Hence, such an ability renders their exploitation as feature ex...

Measuring Human Perception to Improve Handwritten Document Transcription.

IEEE transactions on pattern analysis and machine intelligence
In this paper, we consider how to incorporate psychophysical measurements of human visual perception into the loss function of a deep neural network being trained for a recognition task, under the assumption that such information can reduce errors. A...

Lifelong Teacher-Student Network Learning.

IEEE transactions on pattern analysis and machine intelligence
A unique cognitive capability of humans consists in their ability to acquire new knowledge and skills from a sequence of experiences. Meanwhile, artificial intelligence systems are good at learning only the last given task without being able to remem...

Joint Detection and Matching of Feature Points in Multimodal Images.

IEEE transactions on pattern analysis and machine intelligence
In this work, we propose a novel Convolutional Neural Network (CNN) architecture for the joint detection and matching of feature points in images acquired by different sensors using a single forward pass. The resulting feature detector is tightly cou...

Support Vector Machine Classifier via L Soft-Margin Loss.

IEEE transactions on pattern analysis and machine intelligence
Support vector machines (SVM) have drawn wide attention for the last two decades due to its extensive applications, so a vast body of work has developed optimization algorithms to solve SVM with various soft-margin losses. To distinguish all, in this...

Recent Advances in Large Margin Learning.

IEEE transactions on pattern analysis and machine intelligence
This paper serves as a survey of recent advances in large margin training and its theoretical foundations, mostly for (nonlinear) deep neural networks (DNNs) that are probably the most prominent machine learning models for large-scale data in the com...