Real-Time Detection of Meningiomas by Image Segmentation: A Very Deep Transfer Learning Convolutional Neural Network Approach by Debasmita Das, Chayna Sarkar, Biswadeep Das

“…The performance metrics of the implemented model and confusion matrix for tumor classification indicate the model’s high accuracy in brain tumor classification. …”
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Classification of products based on the uncertainty of supply chain demand: a case study of wineries in Chile by Armando Camino, Juan Pablo Vargas

“…The model has also demonstrated applicability beyond finished goods, such as in-process wine and critical inputs like corks and bottles. This research contributes empirical evidence to close the gap between theory and practice, providing a replicable tool for product segmentation in wine and other industries facing demand complexity. …”
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Deep learning-based image classification for integrating pathology and radiology in AI-assisted medical imaging by Chenming Lu, Jiayin Zhang, Ren Liu

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Automatic GPR detection of grouting defects behind the tunnel shield segments based on wavelet coherence analysis combined with modified Res-RCNN by Dengyi Wang, Ming Peng, Liu Liu, Xiongyao Xie, Zhenming Shi, Yaoying Liang, Jian Shen, Qiyu Wu

“…Ground penetrating radar (GPR), a widely used non-destructive testing technique for detecting grouting defects behind tunnel shield segments, faces challenges like steel rebar interference, low working efficiency, and expert interpretation reliance. …”
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Hierarchical RUL Prediction for Turbofan Engines Based on Health Stage Classification and Change Point-Guided Data Augmentation by Kiymet Ensarioglu

“…This method segments the dataset into pre- and post-change intervals and applies data augmentation both to simulate the truncated nature of the test data—where engines are monitored up to unknown failure points—and to construct a balanced training set that fairly represents both healthy and degraded conditions, thereby improving the robustness and generalization of the classification model. …”
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Learnable Resized and Laplacian-Filtered U-Net: Better Road Marking Extraction and Classification on Sparse-Point-Cloud-Derived Imagery by Miguel Luis Rivera Lagahit, Xin Liu, Haoyi Xiu, Taehoon Kim, Kyoung-Sook Kim, Masashi Matsuoka

“…High-definition (HD) maps for autonomous driving rely on data from mobile mapping systems (MMS), but the high cost of MMS sensors has led researchers to explore cheaper alternatives like low-cost LiDAR sensors. While cost effective, these sensors produce sparser point clouds, leading to poor feature representation and degraded performance in deep learning techniques, such as convolutional neural networks (CNN), for tasks like road marking extraction and classification, which are essential for HD map generation. …”
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Wind during terrestrial laser scanning of trees: Simulation-based assessment of effects on point cloud features and leaf-wood classification by W. Albert, H. Weiser, H. Weiser, R. Tabernig, R. Tabernig, B. Höfle, B. Höfle

“…Understanding these wind effects is crucial since they affect downstream tasks like tree parameter quantification and leaf-wood separation. …”
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Automated note annotation after bioacoustic classification: Unsupervised clustering of extracted acoustic features improves detection of a cryptic owl by Callan Alexander, Robert Clemens, Paul Roe, Susan Fuller

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Mucinous cystic neoplasm of the liver with polypoid nodule prolapsing into the bile duct: a case report and review of literature by Yasuhiro Fukui, Akihiro Murata, Sadatoshi Shimizu, Kayo Sai, Takuma Okada, Tetsuzo Tashima, Shintaro Kodai, Akishige Kanazawa, Takahiro Okuno

“…Abstract Background Mucinous cystic neoplasm of the liver (MCN-L) is a rare cystic tumor as defined by the 2010 World Health Organization classification. MCN-L usually does not communicate with or grow into the bile duct. …”
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Tree Species Detection and Enhancing Semantic Segmentation Using Machine Learning Models with Integrated Multispectral Channels from PlanetScope and Digital Aerial Photogrammetry i... by Arun Gyawali, Mika Aalto, Tapio Ranta

“…These results indicate that a simple boosting model like CatBoost can outperform more complex CNNs for semantic segmentation in young forests.…”
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Detection of Indoor Building Lighting Fixtures in Point Cloud Data using SDBSCAN by Humairah Mansor, Shazmin Aniza Abdul Shukor, Razak Wong Chen Keng, Nurul Syahirah Khalid

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Integrating SAM priors with U-Net for enhanced multiclass cell detection in digital pathology by Zheng Wu, Ji-Yun Yang, Chang-Bao Yan, Cheng-Gui Zhang, Hai-Chao Yang

“…Abstract In digital pathology, the accurate detection, segmentation, and classification of cells are pivotal for precise pathological diagnosis. …”
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Driving Pattern Analysis, Gear Shift Classification, and Fuel Efficiency in Light-Duty Vehicles: A Machine Learning Approach Using GPS and OBD II PID Signals by Juan José Molina-Campoverde, Juan Zurita-Jara, Paúl Molina-Campoverde

“…This study proposes an automatic gear shift classification algorithm in M1 category vehicles using data acquired through the onboard diagnostic system (OBD II) and GPS. …”
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Enhancing pancreatic cancer detection in CT images through secretary wolf bird optimization and deep learning by Sandhya Mekala, Phani Kumar S

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Revolutionizing climbing perch disease management: AI-Driven solutions for sustainable aquaculture by Kosit Sriputhorn, Rapeepan Pitakaso, Surasak Matitopanum, Peerawat Luesak, Surajet Khonjun, Rungwasun Kraiklang, Chakat Chueadee, Sarayut Gonwirat

“…We present the Climbing Perch Disease Detection and Classification System (CPDDCS), employing cutting-edge imaging and deep learning technologies to automate disease detection. …”
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Deep Learning for Traffic Scene Understanding: A Review by Parya Dolatyabi, Jacob Regan, Mahdi Khodayar

“…It examines fundamental techniques such as classification, object detection, and segmentation, and extends to more advanced applications like action recognition, object tracking, path prediction, scene generation and retrieval, anomaly detection, Image-to-Image Translation (I2IT), and person re-identification (Person Re-ID). …”
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Automated Cardiac Disease Prediction Using Composite GAN and DeepLab Model by Sohail Jabbar, Umar Raza, Muhammad Asif Habib, Muhammad Farhan, Saqib Saeed

“…Manual cardiac image interpretation is often subjective and varies significantly among clinicians. However, constraints like limited annotation and model generalization persist. …”
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A deep learning model integrating domain-specific features for enhanced glaucoma diagnosis by Jie Xu, Erkang Jing, Yidong Chai

“…Thus, the relatively high AP values enabled us to calculate the 15 reliable features from each segmented disc and cup. In classification tasks, the DLMDF outperformed other models, achieving superior accuracy, precision, and recall. …”
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High-Precision Tea Plantation Mapping with Multi-Source Remote Sensing and Deep Learning by Yicheng Zhou, Lingbo Yang, Lin Yuan, Xin Li, Yihu Mao, Jiancong Dong, Zhenyu Lin, Xianfeng Zhou

“…It was found that tea plantations at higher altitudes or on north-facing slopes exhibited higher classification accuracy, and that accuracy improves with increasing slope, likely due to simpler land cover types and tea’s preference for shade. …”
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Unlocking Potential Score Insights of Sentimental Analysis with a Deep Learning Revolutionizes by Ibrahim R. Alzahrani

“…Therefore, AI-based approaches are increasingly being adopted for the effective classification of hate and offensive speech. The proposed model incorporates various text preprocessing techniques, such as removing extraneous elements like URLs, emojis, and blank spaces. …”
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