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High-Level Decision Diagrams
In this chapter, we generalize the decision-based concept of logic-level SSBDDs to apply it for modelling digital systems at higher abstraction...
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MLT-Trans: Multi-level Token Transformer for Hierarchical Image Classification
This paper focuses on Multi-level Hierarchical Classification (MLHC) of images, presenting a novel architecture that exploits the “[CLS]”...
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High-Level Synthesis
High-level synthesis (HLS) is the process of compiling a software program into a digital circuit. This chapter provides a view into the HLS design...
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Graph-Level Anomaly Detection via Hierarchical Memory Networks
Graph-level anomaly detection aims to identify abnormal graphs that exhibit deviant structures and node attributes compared to the majority in a...
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Hierarchical Triple-Level Alignment for Multiple Source and Target Domain Adaptation
Domain adaptation aims to bridge the domain gap between the source and target domains. Most existing approaches concentrate on one target domain...
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Document-Level Neural Machine Translation with Hierarchical Modeling of Global Context
Document-level machine translation (MT) remains challenging due to its difficulty in efficiently using document-level global context for translation....
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Hierarchical pose net: spatial hierarchical body tree driven multi-person pose estimation
In this paper, we explore multi-level semantic information of human body structure and propose a paradigm for bottom-up multi-person pose estimation....
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Mining Top-K constrained cross-level high-utility itemsets over data streams
Cross-Level High-Utility Itemsets Mining (CLHUIM) aims to discover interesting relationships between hierarchy levels by introducing the taxonomy of...
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Uncertainty-aware hierarchical reinforcement learning for long-horizon tasks
Hierarchical reinforcement learning excels at dividing difficult task goals into easily achievable subgoals. It provides an effective means to solve...
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Pupil Size Variations Reveal Information About Hierarchical Decision-Making Processes
Introduction : Pupil size is a well-known indicator of low-level decision-making processes. However, it is unclear whether these involuntary eye data...
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A high-level feature channel attention UNet network for cholangiocarcinoma segmentation from microscopy hyperspectral images
Pathological diagnosis is the gold standard for the diagnosis of cholangiocarcinoma. The manual segmentation of pathology sections is time-consuming....
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Big topic modeling based on a two-level hierarchical latent Beta-Liouville allocation for large-scale data and parameter streaming
As an extension to the standard symmetric latent Dirichlet allocation topic model, we implement asymmetric Beta-Liouville as a conjugate prior to the...
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Progressive and multi-level secret image sharing scheme with hierarchical shadows
Multi-level secret image sharing is a scheme combining hierarchical shadows with progressive reconstruction. But in previous schemes, the generated...
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Extracting high-level activities from low-level program execution logs
Modern runtime environments, standard libraries, and other frameworks provide many ways of diagnostics for software engineers. One form of such...
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Attention hierarchical network for super-resolution
Deep neural networks with attention mechanism for super-resolution (SR) have achieved good SR performance by focusing on the high-frequency...
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Hierarchical vectorization for facial images
The explosive growth of social media means portrait editing and retouching are in high demand. While portraits are commonly captured and stored as...
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SEHSNet: Stage Enhancement and Hierarchical Supervision Network for edge detection
Edge detection is a challenging low-level vision task. After a long period of development, there are already edge detectors whose edge recognition...
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Dual Hierarchical Contrastive Learning for Multi-level Implicit Discourse Relation Recognition
Implicit discourse relation recognition (IDRR) is a challenging but vital task in discourse analysis, which aims at classifying logical relations...
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SHCF: A supervised hierarchical clustering approach to remove high density salt and pepper noise from black and white content digital images
When a digital image with a lot of healthy salt and pepper (SP) pixels is corrupted by salt and pepper noises (SPNs) current solutions for SPN...
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Vision Transformers with Hierarchical Attention
This paper tackles the high computational/space complexity associated with multi-head self-attention (MHSA) in vanilla vision transformers. To this...