8 research outputs found
OpenNet: Incremental Learning for Autonomous Driving Object Detection with Balanced Loss
Automated driving object detection has always been a challenging task in
computer vision due to environmental uncertainties. These uncertainties include
significant differences in object sizes and encountering the class unseen. It
may result in poor performance when traditional object detection models are
directly applied to automated driving detection. Because they usually presume
fixed categories of common traffic participants, such as pedestrians and cars.
Worsely, the huge class imbalance between common and novel classes further
exacerbates performance degradation. To address the issues stated, we propose
OpenNet to moderate the class imbalance with the Balanced Loss, which is based
on Cross Entropy Loss. Besides, we adopt an inductive layer based on gradient
reshaping to fast learn new classes with limited samples during incremental
learning. To against catastrophic forgetting, we employ normalized feature
distillation. By the way, we improve multi-scale detection robustness and
unknown class recognition through FPN and energy-based detection, respectively.
The Experimental results upon the CODA dataset show that the proposed method
can obtain better performance than that of the existing methods
When Source-Free Domain Adaptation Meets Label Propagation
Source-free domain adaptation, where only a pre-trained source model is used
to adapt to the target distribution, is a more general approach to achieving
domain adaptation. However, it can be challenging to capture the inherent
structure of the target features accurately due to the lack of supervised
information on the target domain. To tackle this problem, we propose a novel
approach called Adaptive Local Transfer (ALT) that tries to achieve efficient
feature clustering from the perspective of label propagation. ALT divides the
target data into inner and outlier samples based on the adaptive threshold of
the learning state, and applies a customized learning strategy to best fits the
data property. Specifically, inner samples are utilized for learning
intra-class structure thanks to their relatively well-clustered properties. The
low-density outlier samples are regularized by input consistency to achieve
high accuracy with respect to the ground truth labels. In this way, local
clustering can be prevented from forming spurious clusters while effectively
propagating label information among subpopulations. Empirical evidence
demonstrates that ALT outperforms the state of the arts on three public
benchmarks: Office-31, Office-Home, and VisDA
Research Progress in Heterologous Expression, Fermentation and Application of Microbial Transglutaminase
Transglutaminase (TG) is a widely used enzyme with excellent protein cross-linking capacity. TG is commonly found in plants, animals and microorganisms, and microbial TG (mTG) is widely used in industrial production and application because of its good enzymatic properties. This paper describes the physicochemical properties and activation mechanism of mTG, and summarizes recent progress in mTG production by wild and different genetically engineered strains. Meanwhile, the application and potential of mTG in various industrial fields are reviewed. This review is expected to provide a reference and new ideas for research on the potential of mTG for industrial production and application
Effect of perforation shear on viscosity of polymer solution
Polymer flooding is a tertiary oil recovery technology that is very suitable for the characteristics of China’s reservoirs. However, due to the fast flow rate of polymer solution in near-well zone, the shear effect of perforation blasthole and the compacted zone results in serious loss of polymer viscosity. In this paper, the polymer used in Dagang Oilfield is studied by simulation experiment through the shearing process of perforating holes, and the influence of different perforating parameters on polymer viscosity loss is analyzed, so as to provide theoretical basis for the optimization design of perforating technology in field test. The experimental results show that, the shear effect of perforation blasthole on polymer is not obvious, and the viscosity retention rate of polymer solution is greater than 96%. The size and shape of perforation blasthole have no effect on viscosity loss of polymer solution. The shear effect of compacted zone on polymer is obvious, and the viscosity retention rate of polymer solution is lower than 64% for the target block. The viscosity loss of polymer solution increases with flow rate at compacted zone, and the decrease of permeability can increase viscosity loss of polymer solution. The higher the polymer concentration is, the stronger the shear resistance is, while the higher the molecular weight is, the weaker the shear resistance is. It is suggested that perforation gun and perforation method with deep perforation depth and low compaction degree be chosen to reduce the flow rate at compacted zone and viscosity loss of polymer solution
Indirubin-3′-monoxime exhibits potent antiviral and anti-inflammatory effects against human adenoviruses in vitro and in vivo
Human adenovirus (HAdV) infection is a major cause of respiratory disease, yet no antiviral drugs have been approved for its treatment. Herein, we evaluated the antiviral and anti-inflammatory effects of cyclin-dependent protein kinase (CDK) inhibitor indirubin-3′-monoxime (IM) against HAdV infection in cells and a transgenic mouse model. After evaluating its cytotoxicity, cytopathic effect reduction, antiviral replication kinetics, and viral yield reduction assays were performed to assess the anti-HAdV activity of IM. Quantitative real-time polymerase chain reaction (qPCR), quantitative reverse transcription PCR (qRT-PCR), and western blotting were used to assess the effects of IM on HAdV DNA replication, transcription, and protein expression, respectively. IM significantly inhibited HAdV DNA replication as well as E1A and Hexon transcription, in addition to significantly suppressing the phosphorylation of the RNA polymerase II C-terminal domain (CTD). IM mitigated body weight loss, reduced viral burden, and lung injury, decreasing cytokine and chemokine secretion to a greater extent than cidofovir. Altogether, IM inhibits HAdV replication by downregulating CTD phosphorylation to suppress viral infection and corresponding innate immune reactions as a promising therapeutic agent