This article presents LoRaDIP, a novel low-light image enhancement (LLIE) model based on deep image priors (DIPs). While DIP-based enhancement models are known for their zero-shot learning, their expensive computation...
详细信息
This research study presents a new application of reinforcement learning (RL), specifically Proximal Policy Optimization (PPO), in creating immersive virtual reality (VR) games aimed at aiding skill acquisition and em...
详细信息
Quality assessment is a key problem to be resolved in image processing. Few research works have been designed to analyze the quality of images using different techniques. However, the accuracy involved during the proc...
详细信息
Emerging technologies of Agriculture 4.0 such as the Internet of Things (IoT), Cloud Computing, Artificial Intelligence (AI), and 5G network services are being rapidly deployed to address smart farming implementation-...
详细信息
Visible-infrared object detection has attracted increasing attention recently due to its superior performance and cost-efficiency. Most existing methods focus on the detection of strictly-aligned data, significantly l...
详细信息
Visible-infrared object detection has attracted increasing attention recently due to its superior performance and cost-efficiency. Most existing methods focus on the detection of strictly-aligned data, significantly limiting its practical applications. Although several researchers have attempted to explore weakly-aligned visible-infrared object detection, they are limited to small translational deviations and suffer from a low detection speed. This paper first explores non-aligned visibleinfrared object detection with complex deviations in translation, scaling, and rotation, and proposes a fast one-stage detector YOLO-Adaptor, which introduces a lightweight multi-modal adaptor to simultaneously predict alignment parameters and confidence weights between modalities. The adaptor adopts a feature-level alignment during the feature extraction process, ensuring high alignment efficiency. Moreover, we introduce a feature contrastive learning loss to guide the alignment learning of the adaptor, aiming to reduce the representation gap between the two modalities in hyperbolic space to implement feature spatial and distributional consistency. Extensive experiments are conducted on three datasets, including one weakly-aligned and two non-aligned datasets, and the experimental results demonstrate that YOLO-Adaptor could achieve significant performance improvements in terms of speed and accuracy IEEE
Reinforcement learning (RL) and imitation learning (IL) are quite two useful machine learning techniques that were shown to be potential in enhancing navigation performance. Basically, both of these methods try to fin...
详细信息
With the advent of the fourth industrial revolution, data ushered in explosive growth. Federated learning can protect users’ privacy and raw data from being known by third parties. Its client data is only trained loc...
详细信息
The success of vision transformer demonstrates that the transformer structure is also suitable for various vision tasks, including high-level classification tasks and low-level dense prediction tasks. Salient object d...
详细信息
As a deep learning network with an encoder-decoder architecture,UNet and its series of improved versions have been widely used in medical image segmentation with great ***,when used to segment targets in 3D medical im...
详细信息
As a deep learning network with an encoder-decoder architecture,UNet and its series of improved versions have been widely used in medical image segmentation with great ***,when used to segment targets in 3D medical images such as magnetic resonance imaging(MRI),computed tomography(CT),these models do not model the relevance of images in vertical space,resulting in poor accurate analysis of consecutive slices of the same *** the other hand,the large amount of detail lost during the encoding process makes these models incapable of segmenting small-scale tumor *** at the scene of small-scale target segmentation in 3D medical images,a fully new neural network model SUNet++is proposed on the basis of UNet and UNet++.SUNet++improves the existing models mainly in three aspects:1)the modeling strategy of slice superposition is used to thoroughly excavate the three dimensional information of the data;2)by adding an attention mechanism during the decoding process,small scale targets in the picture are retained and amplified;3)in the up-sampling process,the transposed convolution operation is used to further enhance the effect of the *** order to verify the effect of the model,we collected and produced a dataset of hyperintensity MRI liver-stage images containing over 400 cases of liver *** results on both public and proprietary datasets demonstrate the superiority of SUNet++in small-scale target segmentation of three-dimensional medical images.
As industrialization and informatization becomemore deeply intertwined,industrial control networks have entered an era of *** connection between industrial control networks and the external internet is becoming increa...
详细信息
As industrialization and informatization becomemore deeply intertwined,industrial control networks have entered an era of *** connection between industrial control networks and the external internet is becoming increasingly close,which leads to frequent security *** paper proposes a model for the industrial control *** includes a malware containment strategy that integrates intrusion detection,quarantine,and ***,the role of keynodes in the spreadofmalware is studied,a comparisonexperiment is conducted to validate the impact of the containment *** addition,the dynamic behavior of the model is analyzed,the basic reproduction number is computed,and the disease-free and endemic equilibrium of the model is also obtained by the basic reproduction ***,through simulation experiments,the effectiveness of the containment strategy is validated,the influence of the relevant parameters is analyzed,and the containment strategy is *** otherwords,selective immunity to key nodes can effectively suppress the spread ofmalware andmaintain the stability of industrial control *** earlier the immunization of key nodes,the *** the time exceeds the threshold,immunizing key nodes is almost *** analysis provides a better way to contain the malware in the industrial control network.
暂无评论