AI-Driven Framework for Recognition of Guava Plant Diseases through Machine Learning from DSLR Camera Sensor Based High Resolution Imagery by Ahmad Almadhor, Hafiz Tayyab Rauf, Muhammad Ikram Ullah Lali, Robertas Damaševičius, Bader Alouffi, Abdullah Alharbi

“…Furthermore, color (RGB, HSV) histogram and textural (LBP) features are applied to extract rich, informative feature vectors. …”
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Can Separation Enhance Fusion? An Efficient Framework for Target Detection in Multimodal Remote Sensing Imagery by Yong Wang, Jiexuan Jia, Rui Liu, Qiusheng Cao, Jie Feng, Danping Li, Lei Wang

“…Furthermore, small-target detection remains a critical challenge in remote sensing image analysis, as small targets occupy only a few pixels, making feature extraction difficult and prone to errors. …”
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Detection of disease on nasal breath sound by new lightweight architecture: Using COVID-19 as an example by Jiayuan She, Lin Shi, Peiqi Li, Ziling Dong, Renxing Li, Shengkai Li, Liping Gu, Zhao Tong, Zhuochang Yang, Yajie Ji, Liang Feng, Jiangang Chen

“…Additional feature selection was performed using random forest (RF) and principal component analysis (PCA) for dimensionality reduction. …”
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Explaining neural networks for detection of tropical cyclones and atmospheric rivers in gridded atmospheric simulation data by T. Radke, S. Fuchs, C. Wilms, I. Polkova, I. Polkova, I. Polkova, M. Rautenhaus, M. Rautenhaus

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Cervical Cancer Detection Using Deep Neural Network and Hybrid Waterwheel Plant Optimization Algorithm by Sarah A. Alzakari, Amel Ali Alhussan, S.K. Towfek, Marwa Metwally, Dina Ahmed Salem

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Employing convolutional neural networks and explainable artificial intelligence for the detection of seizures from electroencephalogram signal by Tamilarasi Kathirvel Murugan, Anush Kameswaran

“…To identify the EEG data, the proposed system combines deep learning models with feature extraction technique. Model visualization and XAI approaches like feature importance analysis from SHAP values offer clear insights into the model's decision-making process. …”
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Investigating the effects of Gaussian noise on epileptic seizure detection: The role of spectral flatness, bandwidth, and entropy by Nuri Ikizler, Gunes Ekim

“…This study investigates the effect of Gaussian noise on the classification of EEG signals from five classes in the Bonn University EEG dataset for epileptic seizure detection, using Power Spectral Density features. The EEG data are pre-processed with a low-pass filter at a cutoff frequency of 40 Hz, and a total of 11 features, including spectral flatness difference, spectral bandwidth difference, and entropy difference, are extracted. …”
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Hyperspectral Detection of Metal Element Concentration in Vegetation Canopies: A Case Study of Fe and Mo by Daming Wang, Veronika Kopačková-Strnadová, Bo Zhang, Jing Zhang, Feicui Wang, Junquan Yang

“…Regarding the wheat spectral analysis, the absorption features at specified wavelengths were identified as significant for creating valid linear models to analyze the effect of Fe and Mo in wheat leaf and spike spectra. …”
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Salient object detection dataset with adversarial attacks for genetic programming and neural networksMendeley Data by Matthieu Olague, Gustavo Olague, Roberto Pineda, Gerardo Ibarra-Vazquez

“…However, security concerns about its robustness to malicious and imperceptible perturbations have drawn attention since humans or machines can change the predictions of programs entirely. Salient object detection is a research area where deep convolutional neural networks have proven effective but whose trustworthiness represents a significant issue requiring analysis and solutions to hackers' attacks. …”
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EEG-based brain age prediction in infants–toddlers: Implications for early detection of neurodevelopmental disorders by Winko W. An, Aprotim C. Bhowmik, Charles A. Nelson, Carol L. Wilkinson

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Fast COVID-19 Detection from Chest X-Ray Images Using DCT Compression by Fatma Taher, Reem T. Haweel, Usama M. H. Al Bastaki, Eman Abdelwahed, Tariq Rehman, Tarek I. Haweel

“…Currently, real-time quantitative reverse transcription-PCR (rqRT-PCR) is popular for coronavirus detection due to its high specificity, simple quantitative analysis, and higher sensitivity than conventional RT-PCR. …”
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A Study on Instantaneous Time-Frequency Methods for Damage Detection of Nonlinear Moment-Resisting Frames by Ehsan Darvishan, Gholamreza Ghodrati Amiri, Pedram Ghaderi

“…A probabilistic approach is implemented to investigate capability of the procedure for different ground motion records using incremental dynamic analysis. Results show that frequency is not an appropriate feature to detect damage in nonlinear structures.…”
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Dual-Model Synergy for Fingerprint Spoof Detection Using VGG16 and ResNet50 by Mohamed Cheniti, Zahid Akhtar, Praveen Kumar Chandaliya

“…To overcome this limitation, our approach leverages the high-resolution feature extraction of VGG16 and the deep layer architecture of ResNet50 to capture a more comprehensive range of features for improved spoof detection. …”
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Enhancing Brain Tumor Detection: A Comparative Study of CNN Architectures Using MRI Data by Zhu Zhimeng

“…VGG19-BMT incorporates targeted optimizations, including adjustments to convolutional layers and improved feature extraction modules. A systematic comparative analysis of VGG19-BMT and traditional CNN models was conducted using the Kaggle dataset “Brain MRI Images for Brain Tumor Detection.” …”
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A novel fusion architecture for detecting Parkinson’s Disease using semi-supervised speech embeddings by Tariq Adnan, Abdelrahman Abdelkader, Zipei Liu, Ekram Hossain, Sooyong Park, Md Saiful Islam, Ehsan Hoque

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Small Target Detection Algorithm for UAV Aerial Images Based on Improved YOLOv7-tiny by ZHANG Guanghua, LI Congfa, LI Gangying, LU Weidang

“…Among these, the pedestrian, people, and motor categories show especially strong detection performance. 4) The detection performance of the improved algorithm is verified in real-world scenarios through comparative analysis. …”
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Hybrid deep learning model for accurate and efficient android malware detection using DBN-GRU. by Heena Kauser Sk, Maria Anu V

“…The model extracts static features (permissions, API calls, intent filters) and dynamic features (system calls, network activity, inter-process communication) from Android APKs, enabling a comprehensive analysis of application behavior.The proposed model was trained and tested on the Drebin dataset, which includes 129,013 applications (5,560 malware and 123,453 benign).Performance evaluation against NMLA-AMDCEF, MalVulDroid, and LinRegDroid demonstrated that DBN-GRU achieved 98.7% accuracy, 98.5% precision, 98.9% recall, and an AUC of 0.99, outperforming conventional models.In addition, it exhibits faster preprocessing, feature extraction, and malware classification times, making it suitable for real-time deployment.By bridging static and dynamic detection methodologies, the DBN-GRU enhances malware detection capabilities while reducing false positives and computational overhead.These findings confirm the applicability of the proposed model in real-world Android security applications, offering a scalable and high-performance malware detection solution.…”
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Sensor Array System Based on Electronic Nose to Detect Borax in Meatballs with Artificial Neural Network by Anak Agung Surya Pradhana, Suryani Dyah Astuti, null Fauziah, Perwira Annissa Dyah Permatasari, Riskia Agustina, Ahmad Khalil Yaqubi, Harsasi Setyawati, null Winarno, Cendra Devayana Putra

“…Artificial neural networks (ANNs) and principal component analysis (PCA), which are beneficial for feature extraction and classification, are used to handle the collected data based on machine learning approaches. …”
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Two-stage augmentation for detecting malignancy of BI-RADS 3 lesions in early breast cancer by Huanhuan Tian, Li Cai, Yu Gui, Zhigang Cai, Xianfeng Han, Jianwei Liao, Li Chen, Yi Wang

“…We conducted a comparative analysis between our model and four radiologists in breast imaging diagnosis. …”
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Evaluation of Image Segmentation Methods for In Situ Quality Assessment in Additive Manufacturing by Tushar Saini, Panos S. Shiakolas, Christopher McMurrough

“…Quality assessment, especially for the interior part geometry, relies on post-print inspection techniques unsuitable for real-time in situ analysis. Vision-based approaches could be employed to capture images of any layer during fabrication, and then segmentation methods could be used to identify in-layer features in order to establish dimensional conformity and detect defects for in situ evaluation of the overall part quality. …”
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