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 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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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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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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Deep learning in time series forecasting with transformer models and RNNs by Rogerio Pereira dos Santos, João P. Matos-Carvalho, Valderi R. Q. Leithardt

“…This study demonstrates the potential of neural networks, especially transformers, to improve accuracy, providing a practical and theoretical basis for selecting the most suitable models for predictive applications.…”
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Dual-branch attention network-based stereoscopicvideo compression by TANG Shu, ZHAO Yu, YANG Shuli, XIE Xian-Zhong

“…Compared to traditional stereoscopic video (dual-view) compression methods, deep learning-based stereoscopic video compression coding methods achieve superior rate-distortion performance and have become a popular research focus in recent years. However, most existing deep learning-based stereoscopic video compression networks only use convolutional operations to extract and fuse features, which limits their ability to effectively capture non-repetitive texture details within local areas and cannot capture global features, thus affects the quality of image reconstruction during decoding seriously. …”
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Globally scalable glacier mapping by deep learning matches expert delineation accuracy by Konstantin A. Maslov, Claudio Persello, Thomas Schellenberger, Alfred Stein

“…Here we address this gap and propose Glacier-VisionTransformer-U-Net (GlaViTU), a convolutional-transformer deep learning model, and five strategies for multitemporal global-scale glacier mapping using open satellite imagery. …”
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Enhancing Brain Tumor Detection on MRI Images Using an Innovative VGG-19 Model-Based Approach by Burhan Ergen, Abdullah Şener

“…In a conducted study, a new model was developed by utilizing the VGG-19 architecture, a popular convolutional neural network model, to achieve high accuracy in brain tumor detection. …”
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An Intrusion Detection System over the IoT Data Streams Using eXplainable Artificial Intelligence (XAI) by Adel Alabbadi, Fuad Bajaber

“…Meanwhile, for the six different IoT datasets, in most of the datasets, the CNN and DNN achieve 100% accuracy, further validating the effectiveness of the proposed models. …”
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Screen shooting resistant watermarking based on cross attention by Lianshan Liu, Peng Xu, Qianwen Xue

“…In order to identify the origin of information violations, Screen-Shooting Resistant Watermarking (SSRW) has attracted a lot of attention. Most existing solutions are based on Convolutional Neural Networks (CNNs) for the embedding of watermarks. …”
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Flexible integration of spatial and expression information for precise spot embedding via ZINB-based graph-enhanced autoencoder by Jiacheng Leng, Jiating Yu, Ling-Yun Wu, Hongyang Chen

“…Some regions have intact and clear boundaries, while others exhibit blurred boundaries with high intra-domain expression similarity. However, most domain identification methods do not adequately integrate expression and spatial information to flexibly identify different types of domains. …”
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Towards Explainable Graph Embeddings for Gait Assessment Using Per-Cluster Dimensional Weighting by Chris Lochhead, Robert B. Fisher

“…The latent graph embeddings produced by this framework led to a novel semi-supervised weighting function which quantifies and ranks the most important joint features, which are used to provide a description for each pathology. …”
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