95 research outputs found
BSN++: Complementary Boundary Regressor with Scale-Balanced Relation Modeling for Temporal Action Proposal Generation
Generating human action proposals in untrimmed videos is an important yet
challenging task with wide applications. Current methods often suffer from the
noisy boundary locations and the inferior quality of confidence scores used for
proposal retrieving. In this paper, we present BSN++, a new framework which
exploits complementary boundary regressor and relation modeling for temporal
proposal generation. First, we propose a novel boundary regressor based on the
complementary characteristics of both starting and ending boundary classifiers.
Specifically, we utilize the U-shaped architecture with nested skip connections
to capture rich contexts and introduce bi-directional boundary matching
mechanism to improve boundary precision. Second, to account for the
proposal-proposal relations ignored in previous methods, we devise a proposal
relation block to which includes two self-attention modules from the aspects of
position and channel. Furthermore, we find that there inevitably exists data
imbalanced problems in the positive/negative proposals and temporal durations,
which harm the model performance on tail distributions. To relieve this issue,
we introduce the scale-balanced re-sampling strategy. Extensive experiments are
conducted on two popular benchmarks: ActivityNet-1.3 and THUMOS14, which
demonstrate that BSN++ achieves the state-of-the-art performance.Comment: Submitted to AAAI21. arXiv admin note: substantial text overlap with
arXiv:2007.0988
Data-constrained MHD simulation for the eruption of a filament-sigmoid system in solar active region 11520
The separation of a filament and sigmoid is observed during an X1.4 flare on
July 12, 2012 in solar active region 11520, but the corresponding magnetic
field change is not clear. We construct a data-constrained magnetohydrodynamic
simulation of the filament-sigmoid system with the flux rope insertion method
and magnetic flux eruption code, which produces the magnetic field evolution
that may explain the separation of the low-lying filament and high-lying hot
channel (sigmoid). The initial state of the magnetic model contains a magnetic
flux rope with a hyperbolic flux tube, a null point structure and overlying
confining magnetic fields. We find that the magnetic reconnections at the null
point make the right footpoint of the sigmoid move from one positive magnetic
polarity (P1) to another (P3). The tether-cutting reconnection at the
hyperbolic flux tube occurs and quickly cuts off the connection of the
low-lying filament and high-lying sigmoid. In the end, the high-lying sigmoid
erupts and grows into a coronal mass ejection, while the low-lying filament
stays stable. The observed double J-shaped flare ribbons, semi-circular ribbon,
and brightenings of several loops are reproduced in the simulation, where the
eruption of the magnetic flux rope includes the impulsive acceleration and
propagation phases.Comment: This paper has been accepted for publication in the Ap
ChatEDA: A Large Language Model Powered Autonomous Agent for EDA
The integration of a complex set of Electronic Design Automation (EDA) tools
to enhance interoperability is a critical concern for circuit designers. Recent
advancements in large language models (LLMs) have showcased their exceptional
capabilities in natural language processing and comprehension, offering a novel
approach to interfacing with EDA tools. This research paper introduces ChatEDA,
an autonomous agent for EDA empowered by a large language model, AutoMage,
complemented by EDA tools serving as executors. ChatEDA streamlines the design
flow from the Register-Transfer Level (RTL) to the Graphic Data System Version
II (GDSII) by effectively managing task planning, script generation, and task
execution. Through comprehensive experimental evaluations, ChatEDA has
demonstrated its proficiency in handling diverse requirements, and our
fine-tuned AutoMage model has exhibited superior performance compared to GPT-4
and other similar LLMs
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