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Macsum Aggregation Learning and Missing Values
In recent work, a new kind of aggregation method has been proposed under the name of MacSum aggregation function that can be viewed as an interval...
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Exploiting the untapped functional potential of Memento aggregators beyond aggregation
Web archives capture, retain, and present historical versions of web pages. Viewing web archives often amounts to a user visiting the Wayback Machine...
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Efficient weighted multi-source trust aggregation scheme for edge computing offloading
Edge computing offloading involves moving computational tasks from traditional cloud computing data centers to edge servers or terminal devices...
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Aggregation for Flexible Challenge Response
A real problem use-case represents a challenge. This is usually transformed (reduced) to a model. We expect the model to give a response/solution...
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OmiQnet: Multiscale feature aggregation convolutional neural network for omnidirectional image assessment
Recently, deep learning-based methods for quality assessment of omnidirectional images (OIs) have gained widespread attention. However, existing...
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A generalized multi-skill aggregation method for cognitive diagnosis
Online education brings more possibilities for personalized learning, in which identifying the cognitive state of learners is conducive to better...
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A feature aggregation network for contour detection inspired by complex cells properties
Biological vision mechanism plays a very important role in detecting object contour information, so the research of bio-inspired contour detection...
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A decoder-free feature aggregation network for medical image segmentation
Encoder-decoder structured networks have recently become dominant in medical image segmentation, primarily due to their straightforward architecture....
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Node utilization index-based data routing and aggregation protocol for energy-efficient wireless sensor networks
Data aggregation using the shortest path is a challenging issue in wireless sensor networks. Data aggregation slows the communication process and...
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DuAT: Dual-Aggregation Transformer Network for Medical Image Segmentation
Transformer-based models have been widely demonstrated to be successful in computer vision tasks by modeling long-range dependencies and capturing...
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Dynamic Feature Aggregation for Efficient Video Object Detection
Video object detection is a fundamental yet challenging task in computer vision. One practical solution is to take advantage of temporal information...
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SiamRAAN: Siamese Residual Attentional Aggregation Network for Visual Object Tracking
The Siamese network-based tracker calculates object templates and search images independently, and the template features are not updated online when...
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Smooth Building Footprint Aggregation with Alpha Shapes
We propose a method to continuously aggregate building footprints into generalized polygons. This enables smooth zooming that preserves information...
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Classification of Developmental and Brain Disorders via Graph Convolutional Aggregation
While graph convolution-based methods have become the de-facto standard for graph representation learning, their applications to disease prediction...
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Learning rich feature representation and aggregation for accurate visual tracking
AbstractVisual tracking is a key component of computer vision and has a wide range of practical applications. Recently, the tracking-by-segmentation...
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Diagnosis Then Aggregation: An Adaptive Ensemble Strategy for Keyphrase Extraction
Keyphrase extraction (KE) is a fundamental task in the information extraction, which has recently gained increasing attention. However, when facing...
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Sliding-Window Aggregation Algorithms
Sliding-window aggregation summarizes a collection of recent streaming data, capturing the most recent happenings as well as some history. Algorithms...
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Spatiotemporal smoothing aggregation enhanced multi-scale residual deep graph convolutional networks for skeleton-based gait recognition
Gait recognition has a variety of development potentials, such as noncontact potential. The preference for skeleton-based recognition arises due to...
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Large-Scale Rank Aggregation from Multiple Data Sources Based D3MOPSO Method
Aggregating the search result from multiple data sources is a challenging problem in the metasearch engines. However, the ordinary methods do not...
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SLAP: Simpler, Improved Private Stream Aggregation from Ring Learning with Errors
Private Stream Aggregation (PSA) protocols perform secure aggregation of time-series data without leaking information about users’ inputs to the...
