Nondestructive Detection of Rice Milling Quality Using Hyperspectral Imaging with Machine and Deep Learning Regression by Zhongjie Tang, Shanlin Ma, Hengnian Qi, Xincheng Zhang, Chu Zhang

“…Most multi-task models demonstrated a higher prediction accuracy compared with their corresponding single-task models. …”
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A novel approach for multiclass sentiment analysis on Chinese social media with ERNIE-MCBMA by Youyang Sun, Ziyi Yu, Yuyu Sun, Yaqing Xu, Boming Song

“…Abstract Weibo, one of the most widely used social media platforms in China, sees a vast number of users expressing their opinions and emotional tendencies. …”
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Progressive multi-scale multi-attention fusion for hyperspectral image classification by Hu Wang, Sixiang Quan, Jun Liu, Hai Xiao, Yingying Peng, Zhihui Wang, Huali Li

“…Although hyperspectral image classification methods based on convolutional neural networks (CNN) have noticeably improved performance, there are still certain shortcomings in the extraction of detailed and local features. …”
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Surface and Subsurface Soil Moisture Estimation Using Fusion of SMAP, NLDAS-2, and SOLUS100 Data with Deep Learning by Saman Rabiei, Ebrahim Babaeian, Sabine Grunwald

“…This study developed a convolutional neural network–long short-term memory (ConvLSTM) deep learning model to produce ‘daily’ surface (5 cm) and subsurface (25 cm) SM products (9 km) by integrating SMAP level 3 ancillary data, North American Land Data Assimilation System (NLDAS-2; 12 km) SM, and Soil Landscapes of the United States (SOLUS100) digital maps across the contiguous U.S. …”
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A Novel Metaheuristic-Based Methodology for Attack Detection in Wireless Communication Networks by Walaa N. Ismail

“…The framework used involves developing a lightweight model based on a convolutional neural network with 11 layers, referred to as CSO-2D-CNN, which demonstrates fast learning rates and excellent generalization capabilities. …”
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Effects of Automatic Hyperparameter Tuning on the Performance of Multi‐Variate Deep Learning‐Based Rainfall Nowcasting by Amirmasoud Amini, Mehri Dolatshahi, Reza Kerachian

“…This paper combines different convolutional, long short‐term memory (LSTM)‐based networks and NWPs using ensemble techniques (i.e., bagging, random forest, and adaboost methods) with automatic hyperparameter tuning for multi‐step rainfall nowcasting. …”
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Self-Supervised Keypoint Learning for the Geometric Analysis of Road-Marking Templates by Chayanon Sub-r-pa, Rung-Ching Chen

“…To address this, we propose GeoTemplateKPNet, a novel self-supervised deep-learning framework, built upon Convolutional Neural Networks (CNNs), designed to learn robust, geometrically consistent keypoints specifically in synthetic template images. …”
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Multi-model Approach for Tree Detection and Classification in Wallonia Region (Belgium) by N. Dimarco, B. Bartiaux, L. Andreani, R. Schlögel

“…A Faster R-CNN model trained for tree detection achieved a F1 score of 0.828 and a mAP@50 of 0.827, effectively locating tree crowns under varying illumination and phenological conditions. Meanwhile, a convolutional neural network (CNN) for species classification attained an overall accuracy of 0.937, accurately distinguishing most species and age classes. …”
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UniFlow: Unified Normalizing Flow for Unsupervised Multi-Class Anomaly Detection by Jianmei Zhong, Yanzhi Song

“…We adopt multi-cognitive convolutional networks with high capacity to construct the coupling layers within the normalizing flow model for more effective multi-class distribution modeling. …”
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Modeling Terrestrial Net Ecosystem Exchange Based on Deep Learning in China by Zeqiang Chen, Lei Wu, Nengcheng Chen, Ke Wan

“…The model was also compared with the random forest, long short-term memory, deep neural network, and convolutional neural networks (1D) models to distinguish it from previous shallow machine learning models to estimate NEE, and the results show that deep learning models have great potential in NEE modeling. …”
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Micro-Mobility Safety Assessment: Analyzing Factors Influencing the Micro-Mobility Injuries in Michigan by Mining Crash Reports by Baraah Qawasmeh, Jun-Seok Oh, Valerian Kwigizile

“…The results suggest that roads with speed limits exceeding 40 mph are the most significant factor in determining the severity of micro-mobility injuries. …”
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Enhancing Stock Price Forecasting with CNN-BiGRU-Attention: A Case Study on INDY by Madilyn Louisa, Gumgum Darmawan, Bertho Tantular

“…The method applied a hybrid model combining a Convolutional Neural Network (CNN), Bidirectional Gated Recurrent Unit (BiGRU), and an Attention Mechanism (AM) to address the nonlinear, volatile, and noisy characteristics of stock data. …”
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UETT4K Anti-UAV: A Large Scale 4K Benchmark Dataset for Vision-Based Drone Detection in High-Resolution Imagery by Mughees Sarwar Awan, Syed Azhar Ali Zaidi, Junaid Mir

“…Vision-based approaches, especially those employing deep convolutional neural networks (DCNNs), show great promise in addressing the need for an accurate and cost-effective drone detection system. …”
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Modeling energy consumption indexes of an industrial cement ball mill for sustainable production by Saeed Chehreh Chelgani, Rasoul Fatahi, Ali Pournazari, Hamid Nasiri

“…The airlift current and separator variables ranked the most effective operating factors on the mill energy consumption indexes. …”
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Enhancing breast cancer prediction through stacking ensemble and deep learning integration by Fatih Gurcan

“…Breast cancer is one of the most common types of cancer in women and is recognized as a serious global public health issue. …”
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Comparison, optimization and application of multiple prestack inversion algorithm for intermediate basic volcanic reservoirs: A case study of Huoshiling Formation in Chaganhua area by LI Ruilei,CAO Lei,FAN Xuepei,FENG Xiaohui,LI Ning

“…Currently, the most widely used pre-stack simultaneous inversion algorithm is based on the Zoeppritz equation approximation of isotropic horizontal media. …”
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AI-Assisted identification of sex-specific patterns in diabetic retinopathy using retinal fundus images. by Parsa Delavari, Gulcenur Ozturan, Eduardo V Navajas, Ozgur Yilmaz, Ipek Oruc

“…Here we examine whether DR manifests differently in male and female patients, using a dataset of retinal images and leveraging convolutional neural networks (CNN) integrated with explainable artificial intelligence (AI) techniques. …”
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State of Charge Estimation in Li-Ion Batteries Using a Parallel LSTM-Based Approach: The Impact of Modeling Based on Operating States by Osman Ozer, Hayri Arabaci

“…Deep learning has emerged as one of the most widely used approaches in machine learning. …”
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Chess Position Evaluation Using Radial Basis Function Neural Networks by Dimitrios Kagkas, Despina Karamichailidou, Alex Alexandridis

“…The game of chess is the most widely examined game in the field of artificial intelligence and machine learning. …”
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PCB Electronic Component Soldering Defect Detection Using YOLO11 Improved by Retention Block and Neck Structure by Youzhi Xu, Hao Wu, Yulong Liu, Xing Zhang

“…Printed circuit board (PCB) assembly, on the basis of surface mount electronic component welding, is one of the most important electronic assembly processes, and its defect detection is also an important part of industrial generation. …”
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