Deep learning applications for real-time and early detection of fall armyworm, African armyworm, and maize stem borer by Ivan Oyege, Harriet Sibitenda, Maruthi Sridhar Balaji Bhaskar

“…This study aims to evaluate and identify the most accurate and robust DL models in detecting and classifying these three significant agricultural pests. …”
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Graph-Based Adaptive Network With Spatial-Spectral Features for Hyperspectral Unmixing by Hua Dong, Xiaohua Zhang, Jinhua Zhang, Hongyun Meng, Licheng Jiao

“…Thus, we integrate a convolutional neural network to learn local discriminative spatial-spectral features. …”
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Coral reef detection using ICESat-2 and machine learning by Gabrielle A. Trudeau, Kim Lowell, Jennifer A. Dijkstra

“…Coral reefs, among the most vulnerable ecosystems, traditionally employ monitoring techniques that are labor-intensive and costly, prompting the exploration of remote sensing as a cost-effective alternative. …”
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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

“…By providing a comparative analysis, this study aims to guide researchers and clinicians in selecting the most suitable approach for cancer classification tasks. …”
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A Novel Skin Cancer Detection Approach Using Deep Learning Algorithm with Image Segmentation Filters by Awf A. Ramadhan, Omer S. Kareem, Diyar Q. Zeebaree

“… Skin cancer is considered one of the most common and dangerous diseases in the world because so many people do not pay attention to it. …”
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Maturity Classification and Quality Determination of Cherry Using VNIR Hyperspectral Images and Comprehensive Chemometrics by Yuzhen Wei, Siyi Yao, Feiyue Wu, Qiangguo Yu

“…Sweetness and acidity are the two most important indicators to evaluate cherry quality. …”
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Advancements in Hematologic Malignancy Detection: A Comprehensive Survey of Methodologies and Emerging Trends by Rajashree Nambiar, Ranjith Bhat, Balachandra Achar H V

“…This survey systematically examines the state-of-the-art in blood cancer detection through image-based analysis, aimed at identifying the most effective computational strategies and highlighting emerging trends. …”
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Deep learning-based occlusion-aware face mask detection for airborne disease control by Teshome Ayechiluhem Yalew, Sosina M. Gashaw, Aleka Melese Ayalew, Mourad Oussalah

“…The World Health Organization for protection against the spread of airborne diseases has set several guidelines. The most effective preventive measure against airborne diseases, according to the World Health Organization, is wearing masks in public places and crowded areas. …”
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MixtureRS: A Mixture of Expert Network Based Remote Sensing Land Classification by Yimei Liu, Changyuan Wu, Minglei Guan, Jingzhe Wang

“…Our approach employs a 3-D plus heterogeneous convolutional stack to extract rich spectral–spatial features, which are then tokenized and fused via a cross-modality transformer. …”
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Legal Perspectives for Explainable Artificial Intelligence in Medicine - Quo Vadis? by Cătălin-Mihai PESECAN, Lăcrămioara STOICU-TIVADAR

“…Grad-CAM will generate heatmaps based on the gradient from the last layer (because it contains the most information) of a convolutional neural network. …”
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DANC-Net: Dual-Attention and Negative Constraint Network for Point Cloud Classification by Hang Sun, Yuanyue Zhang, Jinmei Shi, Shuifa Sun, Guanqun Sheng, Yirong Wu

“…Nevertheless, in point cloud signal processing, most point cloud classification networks currently do not consider local feature correlation. …”
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A Spectral Interpretable Bearing Fault Diagnosis Framework Powered by Large Language Models by Panfeng Bao, Wenjun Yi, Yue Zhu, Yufeng Shen, Haotian Peng

“…A channel attention-augmented convolutional neural network provides an initial fault type prediction. …”
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A deep learning framework for gender sensitive speech emotion recognition based on MFCC feature selection and SHAP analysis by Qingqing Hu, Yiran Peng, Zhong Zheng

“…Abstract Speech is one of the most efficient methods of communication among humans, inspiring advancements in machine speech processing under Natural Language Processing (NLP). …”
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Evaluation of Deep Learning Models for Polymetallic Nodule Detection and Segmentation in Seafloor Imagery by Gabriel Loureiro, André Dias, José Almeida, Alfredo Martins, Eduardo Silva

“…The initial results suggest that transformer-based methods perform better in most evaluation metrics, but at the cost of higher computational resources. …”
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Multi-physiological signal fusion for objective emotion recognition in educational human–computer interaction by Wanmeng Wu, Enling Zuo, Weiya Zhang, Xiangjie Meng

“…The attention mechanisms provided interpretability by highlighting the most informative physiological features for emotion classification.DiscussionThe developed system offers significant advancements in emotion recognition for educational HCI, enabling more accurate and standardized assessments of teacher emotional states. …”
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Deep Learning-Based Navigation System for Automatic Landing Approach of Fixed-Wing UAVs in GNSS-Denied Environments by Ying-Xi Lin, Ying-Chih Lai

“…This study addresses these problems by combining runway detection and localization methods, YOLOv8 and CNN (convolutional neural network) regression, to demonstrate the robustness of deep learning approaches. …”
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Machine learning-enabled multiscale modeling platform for damage sensing digital twin in piezoelectric composite structures by Somnath Ghosh, Saikat Dan, Preetam Tarafder

“…Abstract Nondestructive evaluation (NDE) of aerospace structures plays a crucial role in their successful operation under harsh environments. Most NDE methods, however, lack real-time in-situ predictive capabilities of evolving damage and are conducted in a post-mortem manner. …”
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Evaluation Model Based on the SGCNiFormer for the Influence of Different Storage Environments on Wheat Quality by Qingchuan Zhang, Zexi Song, Mingwen Bi

“…However, conventional grain storage methods frequently impede the ability to promptly and accurately predict and assess quality changes. Moreover, most storage systems are ineffective in dealing with the impact of temperature and humidity fluctuations on wheat quality, which can potentially lead to quality degradation during storage. …”
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THE APPLICATION OF ARTIFICIAL INTELLIGENCE IN WHITE BLOOD CELL CLASSIFICATION BASED ON MICROSCOPIC IMAGES: A SCOPING REVIEW by Annisa Nur Hasanah, Oktafirani Al Sas, Yosua Darmadi Kosen

“…Findings indicate that the most commonly used method is Convolutional Neural Network (CNN), either standalone or hybrid (e.g., YOLOv5, ResNet, Vision Transformer), achieving accuracies up to 99.7%. …”
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<italic>DynaTrack</italic>: Low-Power Channel-Aware Dynamic Smartphone Tracking Using UWB DL-TDOA by Junyoung Choi, Sagnik Bhattacharya, Joohyun Lee

“…Among the various Ultra-wideband (UWB) ranging methods, the absence of uplink communication or centralized computation makes downlink time-difference-of-arrival (DL-TDOA) localization the most suitable for large-scale industrial deployments. …”
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