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D-Score: A White-Box Diagnosis Score for CNNs Based on Mutation Operators
Convolutional neural networks (CNNs) have been widely applied in many safety-critical domains, such as autonomous driving and medical diagnosis....
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Semiparametric Score-Driven Exponentially Weighted Moving Average Model
Measuring volatility is used in many important financial and economic models. This paper proposes a new semiparametric score driven exponentially...
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Image Aesthetic Score Prediction Using Image Captioning
Different kinds of images induce different kinds of stimuli in humans. Certain types of images tend to activate specific parts of our brain....
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A Tool to Support Propensity Score Weighting for Enhanced Causal Inference in Business Processes
Effectively evaluating the impact of process interventions on business outcomes is crucial for assessing the effectiveness and return on investment...
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Score-Based Generative Models for Medical Image Segmentation Using Signed Distance Functions
Medical image segmentation is a crucial task that relies on the ability to accurately identify and isolate regions of interest in medical images....
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Evaluating Impact
After building your data model, it is time to apply that data model. That is the focus of this chapter, where we will practice tying outputs to...
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Injecting the BM25 Score as Text Improves BERT-Based Re-rankers
In this paper we propose a novel approach for combining first-stage lexical retrieval models and Transformer-based re-rankers: we inject the...
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Research on Hierarchical Teaching Using Propensity Score Weighting-Based Causal Inference Model
The “double reduction” policy is an important initiative of the Party Central Committee to build a strong education country. In this context, how to...
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The Impact of Preprocessing Techniques Towards Word Embedding
In this study, we analyze the performance of various pre-processing methods and classification algorithms on health-related tweet data on Twitter....
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A field- and time-normalized Bayesian approach to measuring the impact of a publication
Measuring the impact of a publication in a fair way is a significant challenge in bibliometrics, as it must not introduce biases between fields and...
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Cognitive Tracing Data Trails: Auditing Data Provenance in Discriminative Language Models Using Accumulated Discrepancy Score
The burgeoning practice of unauthorized acquisition and utilization of personal textual data (e.g., social media comments and search histories) by...
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Injecting the score of the first-stage retriever as text improves BERT-based re-rankers
In this paper we propose a novel approach for combining first-stage lexical retrieval models and Transformer-based re-rankers: we inject the...
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Recognition of score words in freestyle kayaking using improved DTW matching
Voice is the most natural information carrier for human beings, and is likely to become the main method of human–computer interaction in the future....
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Conditional probability table limit-based quantization for Bayesian networks: model quality, data fidelity and structure score
Bayesian Networks (BN) are robust probabilistic graphical models mainly used with discrete random variables requiring discretization and quantization...
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Impact of Feature Normalization on Machine Learning-Based Human Fall Detection
This paper investigates the impact of normalizing data acquired from different multimedia sensor devices on the performance of machine-learning-based...
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Detecting Video Anomalous Events with an Enhanced Abnormality Score
Detecting video anomalous events is vital for human monitoring. Anomalous events usually contain abnormal actions with exaggerated motion and little...
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C-DESERT Score for Arabic Text Summary Evaluation
Text summary evaluation represents an important step after building any summarization system. Despite the important number of metrics that have been...
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Identifying Topics on Social Impact from S&P1500 CSR/ESG Reports
The standard of measuring the social impact of an organization is actually not fully developed in theory and practice. Then what should be contained...
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On kNN Class Weights for Optimising G-Mean and F1-Score
We present two novel theorems that allow for estimating the weight parameter in (weighted) kNN while dealing with imbalanced data. More precisely,...
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Improved gene expression diagnosis via cascade entropy-fisher score and ensemble classifiers
Feature selection is an important technique used in bioinformatics modeling to reduce the dimensionality of high-dimensional data. However,...
