Exploring the transferability of wheat nitrogen status estimation with multisource data and Evolutionary Algorithm-Deep Learning (EA-DL) framework
Accurate and transferable wheat nitrogen status estimation is very important to plant
phenotyping and smart agricultural management. The goal of this study was to establish a …
phenotyping and smart agricultural management. The goal of this study was to establish a …
Towards generalizable diabetic retinopathy grading in unseen domains
Diabetic Retinopathy (DR) is a common complication of diabetes and a leading cause of
blindness worldwide. Early and accurate grading of its severity is crucial for disease …
blindness worldwide. Early and accurate grading of its severity is crucial for disease …
Image captioning based on scene graphs: A survey
J Jia, X Ding, S Pang, X Gao, X Xin, R Hu… - Expert Systems with …, 2023 - Elsevier
Although recent developments in deep learning have brought several tasks closer to human
performance, there is still a significant gap between human and machine performance in …
performance, there is still a significant gap between human and machine performance in …
Mixture-of-experts learner for single long-tailed domain generalization
Domain generalization (DG) refers to the task of training a model on multiple source
domains and test it on a different target domain with different distribution. In this paper, we …
domains and test it on a different target domain with different distribution. In this paper, we …
Test-time style shifting: Handling arbitrary styles in domain generalization
In domain generalization (DG), the target domain is unknown when the model is being
trained, and the trained model should successfully work on an arbitrary (and possibly …
trained, and the trained model should successfully work on an arbitrary (and possibly …
ICDAR 2023 competition on document understanding of everything (DUDE)
This paper presents the results of the ICDAR 2023 competition on Document UnderstanDing
of Everything. DUDE introduces a new dataset comprising 5 K visually-rich documents …
of Everything. DUDE introduces a new dataset comprising 5 K visually-rich documents …
Delving into semantic scale imbalance
Model bias triggered by long-tailed data has been widely studied. However, measure based
on the number of samples cannot explicate three phenomena simultaneously:(1) Given …
on the number of samples cannot explicate three phenomena simultaneously:(1) Given …
TPpred-LE: therapeutic peptide function prediction based on label embedding
H Lv, K Yan, B Liu - BMC biology, 2023 - Springer
Background Therapeutic peptides play an essential role in human physiology, treatment
paradigms and bio-pharmacy. Several computational methods have been developed to …
paradigms and bio-pharmacy. Several computational methods have been developed to …
Variational imbalanced regression: Fair uncertainty quantification via probabilistic smoothing
Existing regression models tend to fall short in both accuracy and uncertainty estimation
when the label distribution is imbalanced. In this paper, we propose a probabilistic deep …
when the label distribution is imbalanced. In this paper, we propose a probabilistic deep …
Complex relation embedding for scene graph generation
Given an input image, scene graph generation (SGG) aims to generate comprehensive
visual relationships between objects in the form of graphs. Recently, more attention to the …
visual relationships between objects in the form of graphs. Recently, more attention to the …