Titlebook: Intelligent Systems and Data Science; Second International Nguyen Thai-Nghe,Thanh-Nghi Do,Salem Benferhat Conference proceedings 2025 The E

晚来的提名

Optimizing Deep Learning for Skin Disease Classification: Leveraging Bayesian Hyperparameter Tuning y addresses the challenges of class imbalance and uneven data distribution in the HAM10000 dataset by proposing a novel approach that integrates advanced data augmentation, model customization, and statistical validation techniques. We employed comprehensive data preprocessing and augmentation strat

Preamble

Medical Image Segmentation by Improved Nested Unetnnections, has become the dominant architecture for this task. However, variations like Nested-Unet are necessary to address the challenge of adapting network size for datasets of varying scales. This study proposes a novel model based on a multilayer Unet architecture that leverages all output feat

dry-eye

Dappled

Developing an AI Vision-Based Approach for Extracting Traffic Information from Imagesation from image sources. It is based on the performance of Transformer models and addresses the challenges and potential solutions in these areas, with a focus on responsible AI deployment. The paper also outlines future research and development directions, such as integrating multi-modal informati

小说

Proposal Feature Fusion Attention Network to Eliminate Fog Effects for Camerais transformed into a sparse feature map and fed into group architectures (.) with multiple skip connections. The output features of . are merged through the feature attention module. The final features will then be passed on to the reconstruction and the remaining global learning structure. Therefo

现代

Terrace

Building a Wastewater Network Graph from Inspection Videoseographic Information Systems (GIS), are often incomplete. Other sources of information are thus required to complete them. Among these, pipe inspection videos, so far mainly used for maintenance and detection of anomalies such as degradation, can be used for this purpose. This article goes in this

伴随而来

Mutual Information-Based Feature Selection for Fault Diagnosis of Induction Motoron motors. Time-domain features extracted from vibration data of induction motors are used as input data for fault diagnosis process. The dataset, formed by the most significant features selected by the proposed method, is divided into training and testing sets and evaluated using supervised learnin

Introduction

Customer Segmentation and Classification Using K-Modes Clustering with Ensemble Learninge segmentation process. Through a comprehensive empirical analysis, conducted on a real-world dataset sourced from Kaggle, the proposed methodology demonstrates superior performance compared to traditional clustering approaches. The experimental results showcase the effectiveness of K-Modes clusteri

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