Infrared and Visible Image Fusion via Residual Interactive Transformer and Cross-Attention Fusion by Liquan Zhao, Chen Ke, Yanfei Jia, Cong Xu, Zhijun Teng

“…The network first introduces a residual dense module to extract shallow features from the input infrared and visible images. …”
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Impact of Safety Signage Placement on Evacuation Behavior in Virtual Fire Scenarios Based on EDA Data by Wenqi Song, Xu Feng, Yu Song

“…Three variables are evaluated, signage height (1m, 0.5m, and 0m), spacing (5m and 10m), and presence of active fire, using a hybrid classification model that integrates an im-proved convolutional neural network (CNN), a Transformer-based sequence encoder, and a multi-layer spiking neural network. …”
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YOLO-BOS: An Emerging Approach for Vehicle Detection with a Novel BRSA Mechanism by Liang Zhao, Lulu Fu, Xin Jia, Beibei Cui, Xianchao Zhu, Junwei Jin

“…First, to bolster the feature-extraction capabilities of the backbone network, we propose a novel Bi-level Routing Spatial Attention (BRSA) mechanism, which selectively filters features based on task requirements and adjusts the importance of spatial locations to more accurately enhance relevant features. …”
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FLPneXAINet: Federated deep learning and explainable AI for improved pneumonia prediction utilizing GAN-augmented chest X-ray data. by Shuvo Biswas, Rafid Mostafiz, Mohammad Shorif Uddin, Muhammad Shahin Uddin

“…The performance of the models was evaluated in a FL environment, with the EDL network achieving the best results: accuracy 97.61%, F1 score 98.36%, recall 98.13%, and precision 98.59%. …”
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Bayesian optimized deep learning and ensemble classification approach for multiclass plant disease identification by Silpa Padmanabhuni, Pradeepini Gera

“…The architecture involves freezing specific layers within Inception v3 to retain essential low-level features while adapting high-level features for the target domain. …”
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Privacy‐preserving speaker verification system based on binary I‐vectors by Aymen Mtibaa, Dijana Petrovska‐Delacrétaz, Jérôme Boudy, Ahmed Ben Hamida

“…These applications usually require users to transmit their recordings, features, or models from their voices over untrusted public networks which stored and processed them on cloud‐based infrastructure. …”
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Deep Learning-based Multi-scale Monitoring of Drought in China with High Spatial Resolution by Y. Peng, J. Liu, Z. Wang, M. Li

“…This study proposes the High Spatial-Resolution SPEI Network (HSR-SPEINet), which integrates environmental factors and remote sensing reflectance data to generate a 1 km resolution SPEI dataset. …”
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Structural resilience of climate regime in the global conflicts by Chuanjing Guan, Jialian Meng, Qinyi Xu

“…We argue that the measurement towards the resilience of such structure shall be based on the evaluation of the ‘three-layer stability’. As proposed in the article, the three-layer structure in the global climate governance system is more resilient to shocks, presented with the two features of structural heterogeneity and institutional redundancy. …”
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Explainable Supervised Learning Models for Aviation Predictions in Australia by Aziida Nanyonga, Hassan Wasswa, Keith Joiner, Ugur Turhan, Graham Wild

“…A comparative evaluation of four machine learning algorithms is conducted for a three-class classification task:—Support Vector Machine (SVM), Logistic Regression (LR), Random Forest (RF), and a deep neural network (DNN) comprising five hidden layers. …”
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Mapping of soil sampling sites using terrain and hydrological attributes by Tan-Hanh Pham, Kristopher Osterloh, Kim-Doang Nguyen

“…The extractor, based on a convolutional neural network (CNN), derives features from spectral images, while the predictor employs self-attention mechanisms to assess feature importance and generate prediction maps. …”
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The applications of CT with artificial intelligence in the prognostic model of idiopathic pulmonary fibrosis by Zeyu Chen, Zheng Lin, Zihan Lin, Qi Zhang, Haoyun Zhang, Haiwen Li, Qing Chang, Jianqi Sun, Feng Li

“…Artificial intelligence (AI) algorithms, including principal component analysis, support vector machine, random survival forest, and convolutional neural network, could be applied to the procedure of IPF prognostic model, that is, region of interest extraction, image feature selection, clinical feature selection, and model construction. …”
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Automated Detection of the Kyphosis Angle Using a Deep Learning Approach: A Cross-Sectional Study on Young Adults by Onur Kocak, Cansel Ficici, Ilknur Ezgi Dogan, Ziya Telatar, Nihan Ozunlu Pekyavas

“…In regard to clinical diagnosis and evaluation methods, high-cost radiological measurements and a variety of non-radiological clinical methods are employed. …”
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Handwritten Text Recognition for Documentary Medieval Manuscripts by Sergio Torres Aguilar, Vincent Jolivet

“…The architecture of the models is based on a Convolutional Recurrent Neural Network (CRNN) coupled with a Connectionist Temporal Classification (CTC) loss. …”
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Advanced leukocyte classification using attention mechanisms and dual channel U-Net architecture by Gauri Kalnoor, Vijayalaxmi Kadrolli

“…A dung beetle with a levy flight strategy assists in streamlined exploration of the search space thereby the detection and delineation of specific regions within images are improved, which results in higher boundary detection accuracy. The evaluation of major quantitative measures such as standard deviation, mean and entropy is comprised in the feature extraction process which offers crucial insights into the structural characteristics of leukocytes. …”
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Indigenous wood species classification using a multi-stage deep learning with grad-CAM explainability and an ensemble technique for Northern Bangladesh. by Ashrafun Zannat, Md Saiful Islam, Md Shahriar Zaman, Sadman Saif

“…It is found that DenseNet121 is the clear winner in our thorough evaluation among seven pre-trained models. The highest accuracy of DenseNet121 is achecived 97.09%. …”
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Construction of a NOx Emission Prediction Model for Hybrid Electric Buses Based on Two-Layer Stacking Ensemble Learning by Jiangyan Qi, Xionghui Zou, Ren He

“…The two-layer stacking ensemble learning model selects eXtreme Gradient Boosting (XGBoost), Random Forest (RF), and an optimized BP neural network as base learners, with a linear regression model as the meta-learner, effectively predicting the instantaneous NOx emission mass of hybrid electric buses. …”
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mmHSE: A Two-Stage Framework for Human Skeleton Estimation Using mmWave FMCW Radar Signals by Jiake Tian, Yi Zou, Jiale Lai

“…The first stage employs a dual-branch network with depthwise separable convolutions and self-attention to extract multi-scale spatiotemporal features from dual-view radar inputs. …”
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The development of a disruption responsive smart room technology with attendance management system by Jennifer P. Juaneza

“…The technology needs to be linked to a network and the internet in order to function as intended. …”
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Census and Analysis of Higher-Order Interactions in Real-World Hypergraphs by Xihang Meng, Xuemeng Zhai, Gaolei Fei, Sheng Wen, Guangmin Hu

“…We propose a systematic framework for hypermotif extraction. This framework features the encoding, census, and evaluation of higher-order patterns, effectively overcoming their inherent complexity and diversity. …”
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WoodenCube: An Innovative Dataset for Object Detection in Concealed Industrial Environments by Chao Wu, Shilong Li, Tao Xie, Xiangdong Wang, Jiali Zhou

“…In addition, we have developed a simple, yet effective, framework for WoodenCube, termed CS-SKNet, which captures strong texture features in the scene by enlarging the network’s receptive field. …”
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