GSBYOLO: A lightweight Multi-Scale fusion network for road crack detection in complex environments by Yuhao Wang, Heran Zhu, Yirong Wang, Jianping Liu, Jun Xie, Bi Zhao, Siyue Zhao

“…Furthermore, through the optimization of the Path Aggregation Network (PAN) and the Bidirectional Feature Pyramid Network (BiFPN), efficient multi-scale feature fusion is achieved, further strengthening the model’s capacity to represent crack features at various scales. …”
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A Theoretical Evaluation in the Context of Actor-Network Theory (ANT) Approaches of Urban Regeneration Implementations: Case Study of Bağcılar District, Istanbul by Ayşegül Baghal, Candan Çinar Çitak

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Comparative Evaluation of Modified Wasserstein GAN-GP and State-of-the-Art GAN Models for Synthesizing Agricultural Weed Images in RGB and Infrared Domain by Shubham Rana, Matteo Gatti

“…This study investigates the application of modified Wasserstein Generative Adversarial Networks with Gradient Penalty (WGAN-GP) to generate synthetic RGB and infrared (IR) datasets to meet the annotation requirements for wild radish (Raphanus raphanistrum). …”
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Performance Evaluation of Hybrid Bio-Inspired and Deep Learning Algorithms in Gene Selection and Cancer Classification by Shahad S. Alkamli, Hala M. Alshamlan

“…Conversely, deep learning models, including convolutional neural networks and autoencoders, demonstrate superior feature extraction but often require larger datasets and higher computational resources. …”
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Towards an intelligent integrated methodology for accurate determination of volume percentages in three-phase flow systems by Abdullah M. Iliyasu, Mohammad Sh. Daoud, Ahmed Sayed Salama, John William Grimaldo Guerrero, Kaoru Hirota

“…The simulated annealing unit systematically evaluates the contribution of each feature to predictive accuracy. …”
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RF-SFAD: A RANDOM FOREST MODEL FOR SELECTIVE FORWARDING ATTACK DETECTION IN MOBILE WIRELESS SENSOR NETWORKS by N Usha Bhanu, Soubhagya Ranjan Mallick, Sreenivasa Rao Chappidi, K Sangeethalakshmi

“…Mobile Wireless Sensor Networks (MWSNs) are highly vulnerable to various security threats due to their open communication channels and deployment in unattended or hostile environments. …”
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Post-disaster building damage assessment based on gated adaptive multi-scale spatial-frequency fusion network by Bo Yu, Yao Sun, Jiansong Hu, Fang Chen, Lei Wang

“…Accurate building damage assessment is crucial for post-disaster response, yet existing methods struggle to capture complex spatial relationships and contextual features needed for distinguishing damage levels. To address this, we propose the Gated Adaptive Multi-scale Spatial-frequency Fusion Network (GAMSF), a two-phase framework for building localization and damage classification. …”
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A Brief Perspective on Deep Learning Approaches for 2D Semantic Segmentation by Shazia Sulemane, Nuno Fachada, João P. Matos-Carvalho

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GhostConv+CA-YOLOv8n: a lightweight network for rice pest detection based on the aggregation of low-level features in real-world complex backgrounds by Fei Li, Yang Lu, Qiang Ma, Shuxin Yin, Rui Zhao

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Experimental trade-offs between different strategies for multihop communications evaluated over real deployments of wireless sensor network for environmental monitoring by Santiago Felici-Castell, Juan J Pérez-Solano, Jaume Segura-Garcia, Miguel García-Pineda, Antonio Soriano-Asensi

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OMSF2: optimizing multi-scale feature fusion learning for pneumoconiosis staging diagnosis through data specificity augmentation by Xueting Ren, Surong Chu, Guohua Ji, Zijuan Zhao, Juanjuan Zhao, Yan Qiang, Yangyang Wei, Yan Wang

“…Existing deep detection models utilize Feature Pyramid Networks (FPNs) to identify objects at different scales. …”
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ResGAT-F: a novel graph neural network-based approach for evaluating landing suitability in the lunar southern polar region by Shibo Wen, Yongzhi Wang, Xingyu Chen, Qizhou Gong, Jianzhong Liu, Xiaoxi Kang, Hengxi Liu, Kai Zhu, Sheng Zhang

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Human motion similarity evaluation based on deep metric learning by Yidan Zhang, Lei Nie

“…Specifically, when extracting the action information feature vectors using the automatic encoder-decoder network model, a sliding window method is used to divide the key point sequences of each limb part into sequence patches, and the action information feature vectors independent of the camera viewpoint and skeleton structure are extracted in a smaller time unit, so as to obtain a more refined action similarity evaluation result. …”
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Enhanced Grey Wolf Optimization (EGWO) and random forest based mechanism for intrusion detection in IoT networks by Saad Said Alqahtany, Asadullah Shaikh, Ali Alqazzaz

“…The selected features are evaluated by using the Random Forest (RF) algorithm to combine multiple decision trees and create an accurate result. …”
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Recognition of Sheep Feeding Behavior in Sheepfolds Using Fusion Spectrogram Depth Features and Acoustic Features by Youxin Yu, Wenbo Zhu, Xiaoli Ma, Jialei Du, Yu Liu, Linhui Gan, Xiaoping An, Honghui Li, Buyu Wang, Xueliang Fu

“…The method included evaluating and filtering the optimal acoustic features, utilizing a customized convolutional neural network (SheepVGG-Lite) to extract Short-Time Fourier Transform (STFT) spectrograms and Constant Q Transform (CQT) spectrograms’ deep features, employing cross-spectrogram feature fusion and assessing classification performance through a support vector machine (SVM). …”
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Enhanced Disc Herniation Classification Using Grey Wolf Optimization Based on Hybrid Feature Extraction and Deep Learning Methods by Yasemin Sarı, Nesrin Aydın Atasoy

“…The proposed approach begins with feature extraction using ResNet50, a deep convolutional neural network known for its robust feature representation capabilities. …”
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Introducing a Novel Figure of Merit for Evaluating Stability of Perovskite Solar Cells: Utilizing Long Short-Term Memory Neural Networks by Zahraa Ismail, Ahmet Sait Alali, Ahmad Muhammad, Mahmoud Ashraf, Sameh O. Abdellatif

“…This study introduces a novel figure of merit for evaluating the stability of perovskite solar cells (PSCs) by employing advanced Long Short-Term Memory (LSTM) neural networks to investigate degradation mechanisms. …”
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A Novel Framework for Improving Soil Organic Carbon Mapping Accuracy by Mining Temporal Features of Time-Series Sentinel-1 Data by Zhibo Cui, Bifeng Hu, Songchao Chen, Nan Wang, Defang Luo, Jie Peng

“…The performance of the partial least squares regression, random forest, and convolutional neural network–long short-term memory (CNN-LSTM) models was evaluated using a 10-fold cross-validation approach. …”
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spaMGCN: a graph convolutional network with autoencoder for spatial domain identification using multi-scale adaptation by Tianjiao Zhang, Hongfei Zhang, Zhongqian Zhao, Saihong Shao, Yucai Jiang, Xiang Zhang, Guohua Wang

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Metabolic pathway activation and immune microenvironment features in non-small cell lung cancer: insights from single-cell transcriptomics by Yanru Liu, Yanru Liu, Yanru Liu, Hanmin Liu, Hanmin Liu, Ying Xiong, Ying Xiong

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