We propose a novel image classification method based on learning hierarchical inter-class structures. Specifically, we first design a fast algorithm to compute the similarity …
In this paper, we study the cooperative path planning and motion coordination problems of the multi-robot system with large number of robots, aiming for practical applications in robotic warehouses and automated transportation systems. Particularly, we solve the life-long planning problem and guarantee the coordination performance in the presence of …
By calculating the similarity in the scale space and judging the information at different scales through the threshold value, the appropriate scale features are dynamically selected, the small-scale features are integrated into the large-scale features, and the dimensionality of the features is reduced.
Joint Hierarchical Priors and Adaptive Spatial Resolution for Efficient Neural Image Compression ... we propose a storage-efficient training strategy for vision classifiers for large-scale ...
Graph sampling frequently compresses a large graph into a limited screen space. This paper proposes a hierarchical structure model that partitions scale-free graphs into three blocks: the core, which captures the underlying community structure, the vertical graph, which represents minority structures that are important in visual analysis, and the …
In this paper, we propose an optimal decomposition approach to large-scale multi-view stereo from an initial sparse reconstruction. The success of the approach depends on the introduction of surface-segmentation-based camera clustering rather than sparse-point-based camera clustering, which suffers from the problems of non-uniform reconstruction …
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A high performance network based on the CNN-RNN paradigm is built which outperforms the original CNN and also the current state-of-the-art and is built on top of any CNN architecture which is primarily designed for leaf-level classification. Objects are often organized in a semantic hierarchy of categories, where fine-level categories are grouped …
This article delves into the hierarchy of large-scale joint crushers and their operational principles. Blow Bars and Impact Plates: At the core of large-scale joint crushers are the blow bars and impact plates.
This article establishes a new multiunmanned aerial vehicle (multi-UAV)-enabled mobile edge computing (MEC) system, where a number of unmanned aerial vehicles (UAVs) are deployed as flying edge clouds for large-scale mobile users. In this system, we need to optimize the deployment of UAVs, by considering their number and locations. At the …
Video Joint Modelling Based on Hierarchical Transformer for Co-Summarization Abstract: Video summarization aims to automatically generate a summary (storyboard or video skim) of a video, which can facilitate large-scale video retrieval and browsing. Most of the existing methods perform video summarization on individual videos, which neglects ...
sbm large scale joint crusher is how ... Find file Blame History Permalink b · f661b88d dushusbm authored Nov 02, 2022. f661b88d ...
hierarchical model for large-scale (marginal) correlation matrix estimation. The model can be easily ex-tended for large-scale partial correlation matrix estimation, and we will discuss this issue in Section 5. We use ˆ to denote the true correlation coefficient between a pair of gene expression profiles (Bickel and Doksum, 2000).
This paper proposes a joint embedding of text and parent category based on hierarchical fine-tuning ordered neurons LSTM (HFT-ONLSTM) for HTC that outperforms the state-of-the-art hierarchical model at a lower computation cost. Text classification has become increasingly challenging due to the continuous refinement of classification label …
This work proposes a Hierarchical Mean-Field learning framework to further improve the performance of existing MF methods, and shows that HMF significantly outperforms existing baselines on both challenging cooperative and mixed cooperative-competitive tasks with different scales of agent populations.
Searching for moving targets in large environments is a challenging task that is relevant in several problem domains, such as capturing an invader in a camp, guarding security facilities, and searching for victims in large-scale search and rescue scenarios. The guaranteed search problem is to coordinate the search of a team of …
The jaw crushers have advantages of large production capacity, large ranges of feeding particle sizes, simple and compact structure, reliable operation, easy …
We propose an end-to-end learning framework based on hierarchical reinforcement learning, called H-TSP, for addressing the large-scale Travelling Salesman Problem (TSP). The proposed H-TSP constructs a solution of a TSP instance starting from the scratch relying on two components: the upper-level policy chooses a small subset of …
Recently, some researchers try to address issues of hierarchical classification in large-scale scenarios by designing the inter-class similarity to construct …
Joint Hierarchical Category Structure Learning and Large-Scale Image Classification Yanyun Qu, Member, IEEE, Li Lin, Fumin Shen, Chang Lu, Yang Wu, Yuan Xie, Member, IEEE, Dacheng Tao, Fellow, IEEE, Abstract—We investigate the scalable image classification prob-lem with a large number of categories. Hierarchical visual data
Request PDF | Joint Hierarchical Category Structure Learning and Large-Scale Image Classification | We investigate the scalable image classification problem with a large number of categories.
This paper proposed an incremental point cloud registration method based on hierarchical graph matching. The proposed method takes two large-scale (millions or more) heterogeneous (point density variations and point distribution differences) point clouds as input and outputs an accurate transformation to register the two point clouds.
Hierarchical visual data structures are helpful for improving the efficiency and performance of large-scale multi-class classification. We propose a novel image …
To accommodate the high mobility and large-scale interconnection requirements of the Internet of Vehicles (IoVs) ... heuristic algorithms are proposed to realize the joint hierarchical placement and configuration of ESs in C-V2X from the aspects of delay-aware, suitability evaluation, and spatial clustering.
However, large-scale problems could not be solved with traditional optimization models and solvers, so this paper deals with hierarchical and other clustering-based algorithms to provide suitable simplification approaches to solve such problems.
We make full use of the pre-known knowledge of environment, and establish a hierarchical semantic map offline for large-scale outdoor environment. The map contains semantic information which is more stable than the commonly used feature points. And the description and recognition methods of locations based on semantic information are …
We investigate the scalable image classification problem with a large number of categories. Hierarchical visual data structures are helpful for improving the efficiency and performance of large-scale multi-class classification. We propose a novel image ...
A joint channel access and power control optimization in large-scale UAV coverage networks is investigated, and a hierarchical mean field game approach is proposed to improve resources utilization efficiency greatly. With the development of the new generation communications, unmanned aerial vehicle base stations (UAV-BSs) have been widely …
Recently, large volumes of false or unverified information (e.g., fake news and rumors) appear frequently in emerging social media, which are often discussed on a large scale and widely disseminated, causing bad consequences. Many studies on rumor detection indicate that the stance distribution of posts is closely related to the rumor veracity. …
The results of the modelling are presented for a baseline case of one industrial-scale jaw crusher and compared to manufacturer data. Future work will include validation and …
In this paper, we propose a multi-agent mixed hierarchical reinforcement learning approach, called MIX-H, for efficient large-scale fleet management by formulating it as a Markov decision process. MIX-H adopts multi-level controllers, including a leader controller and follower controller, for multi-level action learning.
This paper investigates a joint channel access and power control optimization in large-scale UAV coverage networks, and proposes a hierarchical mean …
In this paper, we present a novel hierarchical approach to adversarial attacks targeting Graph Neural Networks (GNNs), tailored to overcome the complexities inherent in large-scale poisoning attacks. Traditional global attack strategies often fail to yield effective results on extensive graph structures. Our innovative method implements a divide-and …
This SpringerBrief covers the technical material related to large scale hierarchical classification (LSHC) and the methods and algorithms that were developed to solve the HC problem in large scale domains, as well as how multiple hierarchies can be leveraged for improving the HC performance.
Hierarchical visual data structures are helpful for improving the efficiency and perfor-mance of large-scale multi-class classification. We propose a novel image classification …
tion progress. The reference [4] utilized hierarchical weighted summation of sub-arrays and proposed a joint sub-array and de-activation (JOINT) hierarchical codebook. Enhanced JOINT (EJOINT) method was further proposed in [5] to avoid an-tenna de-activation. Furthermore, Riemannian optimization-based method [6] and successive closed-form …
Hierarchical Codebook-based Beam Training for Extremely Large-Scale Massive MIMO. Abstract—Extremely large-scale multiple-input multiple-output (XL-MIMO) promises to …
To accommodate the high mobility and large-scale interconnection requirements of the Internet of Vehicles (IoVs) and to realize low-latency and high-r…
Specifically, in this paper, hierarchical clustering and routing (HCR) protocol is proposed to enhance the network lifetime of large-scale WSN by creating balanced clusters. To reduce the computational complexity and control overhead, a hierarchical layered framework (HLF) is designed to provide the joint solution for clustering and routing.
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