Classification of Relevant Information for Drivers in Highly Automated Vehicles by Vladimir V. Savchenko, Veranika V. Litarovich

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COMFormer: classification of maternal-fetal and brain anatomy using a residual cross-covariance attention guided transformer in ultrasound by Sarker, MMK, Singh, VK, Alsharid, M, Hernandez-Cruz, N, Papageorghiou, AT, Noble, JA

“…Experimental results prove that COMFormer outperforms the recent CNN and transformer-based models by achieving 95.64% and 96.33% classification accuracy on maternal-fetal and brain anatomy, respectively.…”

A Hybrid Study for Epileptic Seizure Detection Based on Deep Learning using EEG Data by Abdulkadir Buldu, Kaplan Kaplan, Melih Kuncan

“…Finally, for the classification with the AB-CD-E group, 99.33% classification success rate was achieved by using the CWT method with the Resnet-101 model. …”
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Joint Driver State Classification Approach: Face Classification Model Development and Facial Feature Analysis Improvement by Farkhod Akhmedov, Halimjon Khujamatov, Mirjamol Abdullaev, Heung-Seok Jeon

“…The model’s accuracy was significantly enhanced through advanced image preprocessing techniques, including image normalization, illumination correction, and face hallucination, reaching a 97.33% classification accuracy. The proposed dual-model architecture leverages imagery analysis to detect key drowsiness indicators, such as eye closure dynamics, yawning patterns, and head movement trajectories. …”
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Automated hearing loss type classification based on pure tone audiometry data by Michał Kassjański, Marcin Kulawiak, Tomasz Przewoźny, Dmitry Tretiakow, Jagoda Kuryłowicz, Andrzej Molisz, Krzysztof Koźmiński, Aleksandra Kwaśniewska, Paulina Mierzwińska-Dolny, Miłosz Grono

“…The proposed model achieves 99.33% classification accuracy on datasets outside of training. …”
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Predicting the quality attributes related to geographical growing regions in red-fleshed kiwifruit by data fusion of electronic nose and computer vision systems by Mojdeh Asadi, Mahmood Ghasemnezhad, Adel Bakhshipour, Jamal-Ali Olfati, Mohammad Hossein Mirjalili

“…The PCA-SVM algorithm achieved a 93.33% classification rate for kiwifruits from three regions based on data from individual e-nose and CVS. …”
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Driving Stress Detection Using Multimodal Convolutional Neural Networks with Nonlinear Representation of Short-Term Physiological Signals by Jaewon Lee, Hyeonjeong Lee, Miyoung Shin

“…Additionally, for 10-s signals, the proposed method achieves 92.33% classification accuracy, which is similar to or better than the performance of other methods using long-term signals (over 100 s).…”
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GASTRIC NEUROENDOCRINE TUMOR: WHEN SURGICAL TREATMENT IS INDICATED? by Ademar Caetano Assis Filho, Valdir Tercioti Junior, Nelson Adami Andreollo, José Antonio Possatto Ferrer, João de Souza Coelho Neto, Luiz Roberto Lopes

“…The preoperative upper digestive endoscopy (UDE) indicated a predominance of cases with 0 to 1 lesion (60%), sizing ≥1.5 cm (40%), located in the gastric antrum (53.33%), with ulceration (60%), and Borrmann III (33.33%) classification. The assessment of the surgical specimen indicated a predominance of invasive neuroendocrine tumors (60%), with angiolymphatic invasion in most cases (80%). …”
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Machine Learning Based Automated Segmentation and Hybrid Feature Analysis for Diabetic Retinopathy Classification Using Fundus Image by Aqib Ali, Salman Qadri, Wali Khan Mashwani, Wiyada Kumam, Poom Kumam, Samreen Naeem, Atila Goktas, Farrukh Jamal, Christophe Chesneau, Sania Anam, Muhammad Sulaiman

“…For texture analysis, four types of features—histogram (H), wavelet (W), co-occurrence matrix (COM) and run-length matrix (RLM)—were extracted, and various ML classifiers were employed, achieving 77.67%, 80%, 89.87%, and 96.33% classification accuracies, respectively. To improve classification accuracy, a fused hybrid-feature dataset was generated by applying the data fusion approach. …”
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