Early detection of gray mold on eggplant leaves using hyperspectral imaging technique by FENG Lei, ZHANG De-rong, CHEN Shuang-shuang, FENG Bin, XIE Chuan-qi, CHEN Youyuan, HE Yong

“…Successive projections algorithm (SPA) was executed on 24 feature variables, 13 feature variables in which were extracted as the input of the least square support vector machines (LS-SVM) model, and the accurate rate of the model was 97.5%. …”
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A Hybrid Deep Learning–Based Feature Selection Approach for Supporting Early Detection of Long-Term Behavioral Outcomes in Survivors of Cancer: Cross-Sectional Study by Tracy Huang, Chun-Kit Ngan, Yin Ting Cheung, Madelyn Marcotte, Benjamin Cabrera

“…MethodsWe devised a hybrid deep learning–based feature selection approach to support early detection of negative long-term behavioral outcomes in survivors of cancer. …”
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X-FuseRLSTM: A Cross-Domain Explainable Intrusion Detection Framework in IoT Using the Attention-Guided Dual-Path Feature Fusion and Residual LSTM by Adel Alabbadi, Fuad Bajaber

“…For cross-domain intrusion detection, this paper proposes a novel algorithm, X-FuseRLSTM, a dual-path feature fusion framework that is attention guided and coupled with a residual LSTM architecture. …”
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Analysis of the Relationship Between Scale Invariant Feature Transform Keypoint Properties and Their Invariance to Geometrical Transformation Applied to Cone-Beam Computed Tomograp... by Diletta Pennati, Leonardo Bocchi

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LH-YOLO: A Lightweight and High-Precision SAR Ship Detection Model Based on the Improved YOLOv8n by Qi Cao, Hang Chen, Shang Wang, Yongqiang Wang, Haisheng Fu, Zhenjiao Chen, Feng Liang

“…However, detecting multi-scale ship targets in complex backgrounds leads to issues of false positives and missed detections, posing challenges for lightweight and high-precision algorithms. …”
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A Welding Defect Detection Model Based on Hybrid-Enhanced Multi-Granularity Spatiotemporal Representation Learning by Chenbo Shi, Shaojia Yan, Lei Wang, Changsheng Zhu, Yue Yu, Xiangteng Zang, Aiping Liu, Chun Zhang, Xiaobing Feng

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Detection of Phosphorus in Water by Laser-Induced Breakdown Spectroscopy Based on Liquid-Solid Transformation of Graphite Substrate Combined with PLS-SVR Fusion Quantitative Analys... by Huijie Zhang, Yao Chen, Zongjie Bi, Xiaohua Che, Zhaoshuo Tian

“…To enhance sensitivity in detecting phosphorus in water via laser-induced breakdown spectroscopy (LIBS), this study integrates liquid–solid conversion on graphite substrates with a PLS-SVR fusion algorithm. …”
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Near Real-Time Flood Monitoring Using Multi-Sensor Optical Imagery and Machine Learning by GEE: An Automatic Feature-Based Multi-Class Classification Approach by Hadi Farhadi, Hamid Ebadi, Abbas Kiani, Ali Asgary

“…Land cover classification is then performed using the Random Forest algorithm with the automatically generated training samples. …”
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Comparison of SVM, K-NN, RF, CART, and GNB Algorithms for Water Bodies Detection Using Sentinel-2 Level-2a Imagery in Nakhon Pathom, Thailand by Ni Putu Nita Nathalia, Gede Andra Rizqy Wijaya, Kadek Yota Ernanda Aryanto, Ni Putu Novita Puspa Dewi, Putu Hendra Saputra, Ni Putu Karisma Dewi, Mellisa Damayanti, Kadek Losinanda Prawira

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Multi-convolutional neural network brain image denoising study based on feature distillation learning and dense residual attention by Huimin Qu, Haiyan Xie, Qianying Wang

“…The FDN extracts useful features through two feature distillation blocks, suppresses redundant information, and reduces computational complexity. …”
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LEAF-YOLO: Lightweight Edge-Real-Time Small Object Detection on Aerial Imagery by Van Quang Nghiem, Huy Hoang Nguyen, Minh Son Hoang

“…To address this, we propose LEAF-YOLO, a lightweight and efficient object detection algorithm with two versions: LEAF-YOLO (standard) and LEAF-YOLO-N (nano). …”
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Enhanced mask R-CNN for luminaire detection through brightness balancing and distribution-guided optimization in tunnels by Xiaoqiong Qin, Bintao Xu, Chenchen Wang, Lirui Liu, Linfu Xie, Rong Liu, Mingwei Hu, Xiangsheng Chen

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Ultrafast Laser Beam Profile Characterization in the Front-End of the ELI-NP Laser System Using Image Features and Machine Learning by Tayyab Imran

“…We use centroid tracking to monitor pointing fluctuations, statistical intensity analysis to detect energy instabilities, and Sobel-based edge detection to evaluate beam sharpness and extract structural features from the beam image. …”
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A hybrid deep learning-based intrusion detection system for EV and UAV charging stations by Rosebell Paul, Mercy Paul Selvan

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Integrating near-infrared hyperspectral imaging with machine learning and feature selection: Detecting adulteration of extra-virgin olive oil with lower-grade olive oils and hazeln... by Derick Malavi, Katleen Raes, Sam Van Haute

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Autoimmune gastritis detection from preprocessed endoscopy images using deep transfer learning and moth flame optimization by Fadiyah M. Almutairi, Sara A. Althubiti, Shabnam Mohamed Aslam, Habib Dhahri, Omar Alhajlah, Nitin Mittal

“…This study aims to develop a DL tool to assist clinicians during the AIG examination and hence better detection accuracy is preferred. The merit of the DL model is demonstrated in the individual deep-features and serially concatenated-features and the experimental outcome of this study provides a detection accuracy of 99.33% when the detection is performed with fused-features and K-Nearest Neighbor classifier. …”
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Low Voltage AC Series Arc Fault Detection Method Based on Approximate Entropy for Low Computational Performance Device by Kyoung-Tak Kim, Min-Ho Yoon, Chan-Muk Park, Joung-Hu Park, Sung-Hun Lim

“…The computed Approximate Entropy values for each load and configuration are then used as features in the proposed algorithm. Finally, the algorithm’s performance is evaluated by assessing its series arc fault detection performance and its ability to minimize false detections during normal operation.…”
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SAR Images Change Detection Based on Attention Mechanism-Convolutional Wavelet Neural Network by Jiahui E, Lu Wang, Chunhui Zhao, P. Takis Mathiopoulos, Tomoaki Ohtsuki, Fumiyuki Adachi

“…Comparing this algorithm with seven sets of contrast experiments on six real SAR datasets shows that the accuracy of detecting changes in small regions is 2% –9% better than the classical algorithm.…”
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A Novel Remote Sensing Recognition Using Modified GMM Segmentation and DenseNet by Muhammad Waqas Ahmed, Moneerah Alotaibi, Sultan Refa Alotaibi, Dina Abdulaziz Alhammadi, Asaad Algarni, Ahmad Jalal, Jeongho Cho

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People counting using IR-UWB radar sensors and machine learning techniques by Ange Joel Nounga Njanda, Jocelyn Edinio Zacko Gbadoubissa, Emanuel Radoi, Ado Adamou Abba Ari, Roua Youssef, Aminou Halidou

“…This study aims to detect and count people using impulse radio ultra-wideband radar and machine learning algorithms. …”
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