A Survey on Label-efficient Deep Image Segmentation: Bridging the Gap between Weak Supervision and Dense Prediction

The rapid development of deep learning has made a great progress in image segmentation, one of the fundamental tasks of computer vision. However, the current segmentation algorithms mostly rely on the availability of pixel-level annotations, which are often expensive, tedious, and laborious. To alleviate this burden, the past years have witnessed an increasing attention in building label-efficient, deep-learning-based image segmentation algorithms. This paper offers a comprehensive review on label-efficient image segmentation methods. To this end, we first develop a taxonomy to organize these methods according to the supervision provided by different types of weak labels (including no supervision, inexact supervision, incomplete supervision and inaccurate supervision) and supplemented by the types of segmentation problems (including semantic segmentation, instance segmentation and panoptic segmentation). Next, we summarize the existing label-efficient image segmentation methods from a unified perspective that discusses an important question: how to bridge the gap between weak supervision and dense prediction -- the current methods are mostly based on heuristic priors, such as cross-pixel similarity, cross-label constraint, cross-view consistency, and cross-image relation. Finally, we share our opinions about the future research directions for label-efficient deep image segmentation.Comment: Accepted to IEEE TPAM

Mitochondria-localized AMPK responds to local energetics and contributes to exercise and energetic stress-induced mitophagy

Mitochondria form a complex, interconnected reticulum that is maintained through coordination among biogenesis, dynamic fission, and fusion and mitophagy, which are initiated in response to various cues to maintain energetic homeostasis. These cellular events, which make up mitochondrial quality control, act with remarkable spatial precision, but what governs such spatial specificity is poorly understood. Herein, we demonstrate that specific isoforms of the cellular bioenergetic sensor, 5′ AMP-activated protein kinase (AMPKα1/α2/β2/γ1), are localized on the outer mitochondrial membrane, referred to as mitoAMPK, in various tissues in mice and humans. Activation of mitoAMPK varies across the reticulum in response to energetic stress, and inhibition of mitoAMPK activity attenuates exercise-induced mitophagy in skeletal muscle in vivo. Discovery of a mitochondrial pool of AMPK and its local importance for mitochondrial quality control underscores the complexity of sensing cellular energetics in vivo that has implications for targeting mitochondrial energetics for disease treatment

Research on the impacts and mechanisms of digital strategy on corporate innovation investment

This paper empirically examines the impacts and underlying mechanisms of a digital strategy, along with its four constituent indicators, on enterprise innovation investment. Utilizing a vast sample of companies listed on Chinese stock markets spanning from 2007 to 2022, the study constructs measurement indices for enterprise digital strategies through rigorous text analysis. A multitude of analytical techniques, including panel fixed effects regression, panel mediation effects regression, panel moderation effects regression, and two-stage instrumental variable regression, are employed to investigate these impacts. The findings reveal that a digital strategy exerts a significant and positive influence on firm innovation investment. Furthermore, the mechanism through which this impact occurs is elucidated: digital strategy fosters company innovation investment by augmenting investments in R&D human capital and digital infrastructure. Heterogeneity analysis underscores that the implementation of a digital strategy has a more pronounced effect on company innovation investment under conditions of high financial constraints. Conversely, when institutional investors hold a larger proportion of shares, the impact of digital strategy implementation on company innovation investment is less pronounced. The robustness of these findings is confirmed through additional tests, such as two-stage instrumental variable regression, a panel random effects model, and substitution of the dependent variable. These results collectively offer a scientific rationale for companies to adopt digital strategies and enhance their innovation investment endeavors

COVID-19 and Corporate Performance in the Energy Industry

COVID-19 has had a major impact on the global economy and the energy sector has also been significantly affected by the pandemic.. This paper studies the impact of COVID-19 on corporate performance in the energy industry and finds that COVID-19 has had a significant negative effect on the performance of energy companies. When goodwill impairment was introduced as a moderating variable, companies with goodwill impairment were more strongly affected by the pandemic. Therefore, decision makers at all levels should pay more attention to the impact of COVID-19 on energy companies and take countermeasures in order to mitigate the effects on the energy industry.</jats:p