IEEE transactions on pattern analysis and machine intelligence
Sep 14, 2022
Current multi-object tracking and segmentation (MOTS) methods follow the tracking-by-detection paradigm and adopt 2D or 3D convolutions to extract instance embeddings for instance association. However, due to the large receptive field of deep convolu...
IEEE transactions on pattern analysis and machine intelligence
Sep 14, 2022
Designing effective architectures is one of the key factors behind the success of deep neural networks. Existing deep architectures are either manually designed or automatically searched by some Neural Architecture Search (NAS) methods. However, even...
IEEE transactions on pattern analysis and machine intelligence
Sep 14, 2022
Mammogram mass detection is crucial for diagnosing and preventing the breast cancers in clinical practice. The complementary effect of multi-view mammogram images provides valuable information about the breast anatomical prior structure and is of gre...
IEEE transactions on pattern analysis and machine intelligence
Sep 14, 2022
Text is a new way to guide human image manipulation. Albeit natural and flexible, text usually suffers from inaccuracy in spatial description, ambiguity in the description of appearance, and incompleteness. We in this paper address these issues. To o...
IEEE transactions on pattern analysis and machine intelligence
Sep 14, 2022
This article presents a context-aware tracing strategy (CATS) for crisp edge detection with deep edge detectors, based on an observation that the localization ambiguity of deep edge detectors is mainly caused by the mixing phenomenon of convolutional...
IEEE transactions on pattern analysis and machine intelligence
Sep 14, 2022
Deep visual models are susceptible to adversarial perturbations to inputs. Although these signals are carefully crafted, they still appear noise-like patterns to humans. This observation has led to the argument that deep visual representation is misa...
Molecules (Basel, Switzerland)
Sep 14, 2022
Predicting products of organic chemical reactions is useful in chemical sciences, especially when one or more reactants are new organics. However, the performance of traditional learning models heavily relies on high-quality labeled data. In this wor...
Scientific reports
Sep 14, 2022
Recently, the scenes in large high-resolution remote sensing (HRRS) datasets have been classified using convolutional neural network (CNN)-based methods. Such methods are well-suited for spatial feature extraction and can classify images with relativ...
Scientific reports
Sep 14, 2022
Accurate brain meningioma segmentation and volumetric assessment are critical for serial patient follow-up, surgical planning and monitoring response to treatment. Current gold standard of manual labeling is a time-consuming process, subject to inter...
Scientific reports
Sep 14, 2022
In recent years, a plethora of methods combining neural networks and partial differential equations have been developed. A widely known example are physics-informed neural networks, which solve problems involving partial differential equations by tra...