Advancing Hate Speech Detection in Indonesian Language Using Graph Neural Networks and TF-IDF by Syaikha Amirah Zikrina, Fitriyani

“…This study establishes a robust framework for improving hate speech detection, offering a valuable contribution to safer digital environments.…”
Get full text

RoBERTa-Based Multi-Feature Integrated BiLSTM and CNN Model for Ceramic Review Analysis by LiHua Yang, Jun Wang, WangRen Qiu

“…To address the limitation that the Robustly Optimized BERT Pretraining Approach (RoBERTa) may not effectively capture local dependencies and salient features within the text, we propose a feature fusion framework based on RoBERTa’s multi-output architecture. …”
Get full text

Real time blood detection in CCTV surveillance using attention enhanced InceptionV3 by Adnan Khalil, Fakhre Alam, Dilawar Shah, Irshad khalil, Shujaat Ali, Muhammad Tahir

“…This study proposes a real-time deep learning framework that combines the InceptionV3 architecture with Convolutional Block Attention Modules to enhance spatial and channel-level feature discrimination. …”
Get full text

Prediction of power generation and maintenance using AOC‐ResNet50 network by Yueqiang Chu, Wanpeng Cao, Cheng Xiao, Yubin Song

“…Based on the analysis of the OctConv (Octave Convolution) network structure, the AOctConv (Attention Octave Convolution) convolutional neural network structure is proposed, which is combined with the ResNet50 backbone network to obtain AOC‐ResNet50. …”
Get full text

Enhanced Brain Tumor Segmentation Using CBAM-Integrated Deep Learning and Area Quantification by Rafiqul Islam, Sazzad Hossain

“…Furthermore, the proposed framework enhances segmentation precision while simultaneously incorporating tumor area measurement, making it a comprehensive tool for early-stage tumor analysis. …”
Get full text

Privacy-Oriented Successive Approximation Image Position Follower Processing by Ying Miao, Danyang Shao, Zhimin Yan

“…To solve the detection problem of moving the human body in the dynamic background, the motion target detection module integrates the two ideas of feature information detection and human body model segmentation detection and combines the deep learning framework to complete the detection of the human body by detecting the feature points of key parts of the human body. …”
Get full text

Algorithms for the visual analysis of an environment by an autonomous mobile robot for area cleanup by M. E. Beliakov, S. A. K. Diane

“…The purpose of this work is to develop the underlying algorithmics for the vision system of robots executing area cleaning functions.Methods. Within the framework ofthe proposed structure ofthe system for visual analysis ofthe external environment, algorithms for detecting and classifying objects of various appearance have been developed using convolutional neural networks. …”
Get full text

Complex Network Analytics for Structural–Functional Decoding of Neural Networks by Jiarui Zhang, Dongxiao Zhang, Hu Lou, Yueer Li, Taijiao Du, Yinjun Gao

“…This work proposes a complex network theory framework decoding structure–function coupling by mapping convolutional layers, fully connected layers, and Dropout modules into graph representations. …”
Get full text

Task-Related EEG as a Biomarker for Preclinical Alzheimer’s Disease: An Explainable Deep Learning Approach by Ziyang Li, Hong Wang, Lei Li

“…An interpretable deep learning framework—Interpretable Convolutional Neural Network (InterpretableCNN)—was utilized to identify AD-related EEG features. …”
Get full text

Orbital Behavior Intention Recognition for Space Non-Cooperative Targets Under Multiple Constraints by Yuwen Chen, Xiang Zhang, Wenhe Liao, Guoning Wei, Shuhui Fan

“…To address the issue of misclassification and diminished accuracy that is prevalent in existing intent recognition models for non-cooperative spacecraft due to the omission of environmental influences, this paper presents a novel recognition framework leveraging a hybrid neural network subject to multiple constraints. …”
Get full text

Knowledge Distillation‐Based Zero‐Shot Learning for Process Fault Diagnosis by Yi Liu, Jiajun Huang, Mingwei Jia

“…With unknown faults as a zero‐shot learning problem, this article proposes a method for detecting and isolating unknown faults based on knowledge distillation within a teacher–student framework. Process data and image data are equivalent in their spatiotemporal dimensions, and convolutional neural networks are selected as the teacher model, pretrained on image data. …”
Get full text

Web-Enhanced Vision Transformers and Deep Learning for Accurate Event-Centric Management Categorization in Education Institutions by Khalied M. Albarrak, Shaymaa E. Sorour

“…By categorizing images into five primary event management categories and subcategories, this research provides a robust framework for assessing the social media content generated by KFU’s administrative units. …”
Get full text

Internet of Things and Deep Learning for Citizen Security: A Systematic Literature Review on Violence and Crime by Chrisbel Simisterra-Batallas, Pablo Pico-Valencia, Jaime Sayago-Heredia, Xavier Quiñónez-Ku

“…This study conducts a systematic literature review following the PRISMA framework and the guidelines of Kitchenham and Charters to analyze the application of Internet of Things (IoT) technologies and deep learning models in monitoring violent actions and criminal activities in smart cities. …”
Get full text

Landscape layout characteristics and evaluation of smart buildings based on deep learning algorithms by Li Zhang

“…Based on the landscape layout of intelligent buildings, this study proposes an evaluation framework based on a deep learning algorithm, aiming at improving the quality and efficiency of landscape design through intelligent means. …”
Get full text

Equivariant spherical CNNs for accurate fiber orientation distribution estimation in neonatal diffusion MRI with reduced acquisition time by Haykel Snoussi, Davood Karimi

“…In this study, we propose a rotationally equivariant Spherical Convolutional Neural Network (sCNN) framework tailored for neonatal dMRI. …”
Get full text

Real-time Jordanian license plate recognition using deep learning by Salah Alghyaline

“…This paper aims to develop an accurate ALPR for Jordanian LPs. Two-stage Convolutional Neural Networks (CNNs) are used in the proposed approach, the CNNs are based on the YOLO3 framework. …”
Get full text

A Deep Learning based Hybrid Model for Maternal Health Risk Detection and Multifaceted Emotion Analysis in Social Networks by Geethanjali R., Valarmathi A.

“…Our study addresses this challenge by introducing the maternal health risk factor detection using deep learning approach (MHRFD-DLA), a novel framework that integrates convolutional neural networks, long short-term memory networks, and attention mechanisms. …”
Get full text

Automated Crack Width Measurement in 3D Models: A Photogrammetric Approach with Image Selection by Huseyin Yasin Ozturk, Emanuele Zappa

“…By synthesizing photogrammetry and a convolutional neural network (CNN), the framework eliminates subjectivity in inspections, enhances safety by reducing manual intervention, and provides engineers with dimensionally accurate data for maintenance decisions.…”
Get full text

Multi-Time Scale Scenario Generation for Source–Load Modeling Through Temporal Generative Adversarial Networks by Liang Ma, Shigong Jiang, Yi Song, Chenyi Si, Xiaohan Li

“…To address these issues, this paper proposes a multi-time scale source–load scenario generation method based on temporal convolutional networks and multi-head attention mechanisms within a temporal generative adversarial network framework. …”
Get full text

Hierarchical Information-guided robotic grasp detection by Zeyao Hou, Yueran Zhao, Yutao Jin, Chao Yang, Zongyu He, Xiaoyan Chen

“…GraspFormer features a unique Encoder-Decoder framework that incorporates a Grasp Transformer Block designed to model long-range dependencies while avoiding background interference. …”
Get full text