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Feature Modeling of Distribution Boxes

Feature Modeling of Distribution Boxes - E-Motional Optics & Connectivity
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Exploring feature sparsity for out-of-distribution detection

In this work, our point of departure is to enlarge distinguishability between in-distribution features and OOD data. Consequently, we present a simple yet effective sparsity-regularized (SR)...

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GAM-YOLOv8n: enhanced feature extraction and difficult

By introducing a global attention mechanism, we have suc-cessfully enhanced the feature extraction ability of the model, enabling it to effectively detect changes in the size and posture of distribution

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Dream-Box: Object-wise Outlier Generation for Out-of-Distribution

We therefore introduce Dream-Box, a method that provides a link to object-wise outlier generation in the pixel space for OOD detection. Specifically, we use diffusion models to generate

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Probabilistic Modeling of Deep Features for Out-of-Distribution and

We present a principled approach for detecting out-of-distribution (OOD) and adversarial samples in deep neural networks. Our approach consists in modeling the outputs of the various

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Gray-Box Modeling for Distribution Systems With Inverter-Based

In this paper, we develop a novel gray-box modeling approach for distribution systems with inverter-based resources (IBRs). The proposed gray-box modeling method aims to improve estimation

Gray-Box Modeling for Distribution Systems with Inverter-Based

This endeavor gives rise to a valuable technique known as the gray-box modeling method, which incorporates features of the white-box and black-box models. Implementing prior knowledge in a gray

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Sample-free white-box out-of-distribution detection for deep learning

In this paper, we tackled the challenging task of out-of-distribution (OOD) detection with no data, assuming a white-box access to the network. We firstly introduced several indicators for the task and

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We replace the feature values of features that are not in a coalition with random feature values from the apartment dataset to get a prediction from the machine learning model. If we estimate the Shapley

GAM-YOLOv8n: enhanced feature extraction and difficult example

This improved method provides an efficient and accurate solution for practical detection tasks in smart chemical sites, especially in enhancing feature extraction and processing difficult

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Fault Intelligent Diagnosis for Distribution Box in Hot Rolling Based

To address the issue of timely fault diagnosis and minimize downtime for distribution boxes, this paper introduces a novel intelligent fault diagnosis model for the distribution box.

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