IEEE transactions on pattern analysis and machine intelligence
Aug 4, 2022
Due to lack of data, overfitting ubiquitously exists in real-world applications of deep neural networks (DNNs). We propose advanced dropout, a model-free methodology, to mitigate overfitting and improve the performance of DNNs. The advanced dropout t...
IEEE transactions on pattern analysis and machine intelligence
Aug 4, 2022
We consider the graph link prediction task, which is a classic graph analytical problem with many real-world applications. With the advances of deep learning, current link prediction methods commonly compute features from subgraphs centered at two ne...
IEEE transactions on pattern analysis and machine intelligence
Aug 4, 2022
Deep neural networks are trained so as to achieve a kind of the maximum overall accuracy through a learning process using given training data. Therefore, it is difficult to fix them to improve the accuracies of specific problematic classes or classes...
IEEE transactions on pattern analysis and machine intelligence
Aug 4, 2022
The field of meta-learning, or learning-to-learn, has seen a dramatic rise in interest in recent years. Contrary to conventional approaches to AI where tasks are solved from scratch using a fixed learning algorithm, meta-learning aims to improve the ...
IEEE transactions on pattern analysis and machine intelligence
Aug 4, 2022
As an emerging and challenging problem in the computer vision community, weakly supervised object localization and detection plays an important role for developing new generation computer vision systems and has received significant attention in the p...
IEEE transactions on pattern analysis and machine intelligence
Aug 4, 2022
The light field (LF) reconstruction is mainly confronted with two challenges, large disparity and the non-Lambertian effect. Typical approaches either address the large disparity challenge using depth estimation followed by view synthesis or eschew e...
IEEE transactions on pattern analysis and machine intelligence
Aug 4, 2022
The research in image quality assessment (IQA) has a long history, and significant progress has been made by leveraging recent advances in deep neural networks (DNNs). Despite high correlation numbers on existing IQA datasets, DNN-based models may be...
IEEE transactions on pattern analysis and machine intelligence
Aug 4, 2022
Neural Architecture Search (NAS) has emerged as a promising technique for automatic neural network design. However, existing MCTS based NAS approaches often utilize manually designed action space, which is not directly related to the performance metr...
IEEE transactions on pattern analysis and machine intelligence
Aug 4, 2022
We consider predicting the user's head motion in 360 videos, with 2 modalities only: the past user's positions and the video content (not knowing other users' traces). We make two main contributions. First, we re-examine existing deep-learning appro...
IEEE transactions on pattern analysis and machine intelligence
Aug 4, 2022
We describe a learning-based system that estimates the camera position and orientation from a single input image relative to a known environment. The system is flexible w.r.t. the amount of information available at test and at training time, catering...