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Optimal Granule Combination Selection Based on Multi …
The thinking mode based on granule structure in granular computing essentially simulates the pattern of human thinking to solve problem. Such thinking for the study of knowledge discovery is also of significant importance in cognitive computing. Under such circumstances, the theory of multi-granularity formal concept analysis (MG-FCA) …
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Multi-object optimization design for differential and grading …
Mathematical modeling and optimization of the design parameters of the working chamber and the executive body (roll) of a single-roll gyratory shaft crusher, …
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Multi-granularity Feature Attention Fusion Network for …
To solve the above problems, this paper proposes a multi-granularity feature attention fusion network (MGFAFN) for multi-modal sentiment analysis to mine complex associations between images and their text descriptions.Specifically, the multi-granularity feature attention fusion network proposed in this paper includes feature learning layer, …
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Multiple Granularity Descriptors for Fine-Grained …
Our multiple granularity framework can be learned with the weakest supervision, requiring only image-level label and avoiding the use of labor-intensive bounding box or part annotations. Experimental results on three challenging fine-grained image datasets demonstrate that our approach outperforms state-of-the-art algorithms, including those ...
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Multi-Granularity Batch Sequential Design Method for …
Building upon a foundation of rapidly constructed simulation models, we proposed a multi-granularity batch sequential design method to address the …
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Multi-granularity sequence generation for hierarchical image
Hierarchical multi-granularity image classification is a challenging task that aims to tag each given image with multiple granularity labels simultaneously. Existing methods tend to overlook that different image regions contribute differently to label prediction at different granularities, and also insufficiently consider relationships between …
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HPT Multi-cylinder Hydraulic Cone Crusher
Multiple Cavity Types Meet Various Production Needs. HPT Hydraulic Cone Crusher has several kinds of cavities suitable for medium-fine or fine crushing of materials. Users can freely make choices among different cavities by changing only a few spare parts like the lining plate, truly achieving that a crusher serves multiple purposes.
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Understanding Multi-Granularity for Open-Vocabulary Part …
Open-vocabulary part segmentation (OVPS) is an emerging research area focused on segmenting fine-grained entities based on diverse and previously unseen vocabularies. Our study highlights the inherent complexities of part segmentation due to intricate boundaries and diverse granularity, reflecting the knowledge-based nature of …
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Multi-Action cone crushers MX™ Seri
IC crusher automation ptimize your production eficiency and upt me. It protects the crusher in multiple ways. The process can be started and stopped by press-ing a single …
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MuGE: Multiple Granularity Edge Detection
MuGE: Multiple Granularity Edge Detection Caixia Zhou1, Yaping Huang1*, Mengyang Pu 2, Qingji Guan1, Ruoxi Deng3, Haibin Ling4 1Beijing Key Laboratory of Traffic Data Analysis and Mining, Beijing Jiaotong University 2 North China Electric Power University 3 Wenzhou University 4Stony Brook University {cxzhou,yphuang,qjguan}@bjtu.edu, …
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Title: Towards Unified Multi-granularity Text Detection with
Existing OCR engines or document image analysis systems typically rely on training separate models for text detection in varying scenarios and granularities, leading to significant computational complexity and resource demands. In this paper, we introduce "Detect Any Text" (DAT), an advanced paradigm that seamlessly unifies scene text …
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Design, Fabrication and Testing of a Double Roll Crusher
Comminution is the reduction of solid materials from one average particle size to a smaller average particle size, by crushing, grinding, cutting and vibrating …
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Multiple Granularity Locking in DBMS
1. What is the purpose of multiple granularity locking? Multiple granularity locking allows transactions to lock different levels of granularity, such as the entire database, a table, a page, or a single data item, to improve concurrency and reduce lock contention. 2. How does multiple granularity locking differ from other locking …
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3-D designing of an organic waste crusher
The steps for designing the organic waste crusher involve determining a conceptual physical geometry, conducting mechanical design, and finally, developing a …
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Multi-Granularity Matching Transformer for Text-Based …
Text-based person search aims to retrieve the most relevant pedestrian images from an image gallery based on textual descriptions. Most existing methods rely on two separate encoders to extract the image and text features, and then elaborately design various schemes to bridge the gap between image and text modalities. However, the shallow …
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Multi-granularity interaction model based on pinyins and …
Semantic matching plays a critical role in many downstream tasks of natural language processing. Existing semantic matching methods, which focus on learning sentence semantic features based on character and word granularities, neglect to consider the special characteristics of Chinese, e.g., pinyins and radicals. However, both pinyins …
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Multiple Granularity Descriptors for Fine-Grained …
Multiple Granularity Descriptors for Fine-grained Categorization Dequan Wang1, Zhiqiang Shen1, Jie Shao1, Wei Zhang1, Xiangyang Xue1 and Zheng Zhang2 1Shanghai Key Laboratory of Intelligent Information Processing, School of Computer Science, Fudan University 2Department of Computer Science, New York University Shanghai …
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Multi-granularity Textual Adversarial Attack with Behavior …
%0 Conference Proceedings %T Multi-granularity Textual Adversarial Attack with Behavior Cloning %A Chen, Yangyi %A Su, Jin %A Wei, Wei %Y Moens, Marie-Francine %Y Huang, Xuanjing %Y Specia, Lucia %Y Yih, Scott Wen-tau %S Proceedings of the 2021 Conference on Empirical Methods in Natural Language …
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Multi-granularity Temporal Question Answering over …
%0 Conference Proceedings %T Multi-granularity Temporal Question Answering over Knowledge Graphs %A Chen, Ziyang %A Liao, Jinzhi %A Zhao, Xiang %Y Rogers, Anna %Y Boyd-Graber, Jordan %Y Okazaki, Naoaki %S Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long …
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Model-Driven Compression for Digital Human Using Multi …
In this paper, we propose a novel digital human model-driven compression framework by using multi-granularity representations. A coarse-grained layer based on the Skinned Multi-Person Linear model (SMPL) is introduced to extract general structures, while the normal images are used to represent fine-grained details via pose consistency-based ...
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A Multi-Granularity Scene Segmentation Network for Human …
Human-robot collaboration (HRC) has been considered as a promising paradigm towards futuristic human-centric smart manufacturing, to meet the thriving needs of mass personalization. In this context, existing robotic systems normally adopt a single-granularity semantic segmentation scheme for environment perception, which lacks the flexibility to …
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Robust Neural Relation Extraction via Multi-Granularity …
In this paper, we propose a novel and robust neural approach to deal with both problems by reducing influences of the multi-granularity noises. Three levels of noises from word, sentence until knowledge type are carefully considered in this work. We first initiate a question-answering based relation extractor (QARE) to remove noisy words in a ...
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Jaw Crusher Diagram: Simplified Guide
The jaw crusher diagram is instrumental when it comes to adjustments for altering the granularity of the output. One critical metric is the Closed Side Setting (CSS)—the smallest gap between the jaws during the crushing cycle. Adjusting CSS is a straightforward affair and can make a significant difference in your output's size and quality.
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Multi-Granularity Modeling and Aggregation of Design …
A method of DR multi-granularity modeling with two-stage aggregation is proposed, by which the resource granularity is increased and dynamic design capability …
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Fine-grained image recognition via trusted multi-granularity …
Fine-grained image recognition (FGIR) is more challenging than general image recognition tasks due to the inherently subtle object variation. The existing FGIR methods are mainly based on single-granularity feature fusion, the extracted fused features often cannot fully reflect the characteristics of the object, and the recognition …
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MGRE: A Multi-Granularity Representation Enhancement …
In recent years, many works have concentrated on designing models from the perspective of using the information of the question and options at a large granularity level. However, few studies have explored how the model uses the information to find the correct answer at a fine granularity level or a multi-granularity level.
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BR-HIDF: An Anti-Sparsity and Effective Host Intrusion …
Then, we design a multi-granularity feature extraction method (MGFE), which also meets the prerequisite mathematical conditions of the anti-ST. By applying this method, we effectively reduce the size of the feature space and minimize the number of generated features, thus mitigating sparsity. Furthermore, leveraging this approach, we …
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Optimal Granule Combination Selection Based on Multi …
In this paper, in order to solve the problem of three-dimensional data granularity, the idea of granularity of attributes is first introduced into triadic contexts on …
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Multiple Granularity Locking in DBMS
Multiple Granularity Locking in DBMS - DBMS (Database Management System) is used for effective management of data. It enables multiple users to access the same data without compromising its consistency and integrity. A Challenge in DBMS is locking, which is used to prevent multiple users from accessing the same data …
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Multi-Granularity Contrastive Learning for Graph with …
Moreover, in graph contrastive learning, leveraging multiple granularity views can offer diverse levels of abstraction in terms of information and structures, enabling models to gain a deeper understanding and analysis of the structures and properties of graphs. This is an aspect that has received relatively less attention in existing research.
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