Convolutional Edge Constraint-Based U-Net for Salient Object Detection by Le Han, Xuelong Li, Yongsheng Dong

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Cyberbullying Detection in Arabic Text Using Different Deep Learning Approaches by Humera Shaziya

“…Addressing this issue requires advanced emotional and sentiment analysis techniques. In this study, the ArCyC (Arabic Cyberbullying Corpus) were integrated with Twitter data to develop robust models for cyberbullying detection. …”
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Detection of Abnormal Symptoms Using Acoustic-Spectrogram-Based Deep Learning by Seong-Yoon Kim, Hyun-Min Lee, Chae-Young Lim, Hyun-Woo Kim

“…In this study, we propose a method for detecting abnormal symptoms by converting acoustic data into spectrogram representations and applying a deep learning model. …”
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Medical Image Segmentation for Anomaly Detection Using Deep Learning Techniques by Bibat Thokar, Binod Sapkota, Babu R. Dawadi, Shashidhar R. Joshi

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DETECTION OF AUTOREACTIVE CLASS M ANTIBODIES IN PATIENTS WITH RESPIRATORY VIRAL INFECTIONS by V. Z. Krivitskaya, M. V. Sverlova, V. F. Sukhovetskaya, N. I. Lvov, I. A. Vassilieva, A. A. Sominina

“…The aim of this study was to detect some features of autoreactive IgM production that interact with IgGs and normal human cellular antigens in blood sera of patients with acute respiratory viral infections caused by various factors, dependent on their age and clinical features of disease. …”
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Contextual information based anomaly detection for multi-scene aerial videos by Girisha S, Ujjwal Verma, Manohara M M. Pai, Radhika M. Pai

“…The proposed system holistically utilizes contextual, temporal, and appearance features for the accurate detection of anomalies. A novel feature descriptor is designed to effectively capture contextual information necessary for analyzing multi-scene videos. …”
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Clinical and dermoscopic assessment of angiosarcoma: a diagnostic classification for early detection by Vincenzo De Giorgi, Biancamaria Zuccaro, Giovanni Cecchi, Gabriella Perillo, Ignazio Stanganelli, Piero Covarelli

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Skin cancer detection using dermoscopic images with convolutional neural network by Khadija Nawaz, Atika Zanib, Iqra Shabir, Jianqiang Li, Yu Wang, Tariq Mahmood, Amjad Rehman

“…This work is a testament to the importance of specificity in medical image analysis regarding skin cancer detection.…”
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Enhanced water saturation estimation in hydrocarbon reservoirs using machine learning by Ali Akbari, Ali Ranjbar, Yousef Kazemzadeh, Dmitriy A. Martyushev

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A satellite navigation spoofing interference detection method based on LSTM by ZHAO Shen, HUANG Wenna, QIN Yemei, LIAO Yifei, YANG Lingling

“…Based on the analysis of the effect of spoofing interference on the receiver loop, the direct and indirect information in the tracking loop was selected as the spoofing detection feature parameters. …”
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A Satellite Navigation Spoofing Interference Detection Method Based on LSTM by ZHAO Shen, HUANG Wenna, QIN Yemei, LIAO Yifei, YANG Lingling

“…Based on the analysis of the effect of spoofing interference on the receiver loop, the direct and indirect information in the tracking loop is selected as the spoofing detection feature parameters; the feature parameters are preprocessed using the sliding window technique, and the training and test sets are constructed according to the time series to ensure the temporal relevance of the features. …”
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Multichannel convolutional transformer for detecting mental disorders using electroancephalogrpahy records by Mamadou Dia, Ghazaleh Khodabandelou, Syed Muhammad Anwar, Alice Othmani

“…These results underscore the potential of our proposed architecture in delivering accurate and reliable mental disorder detection through EEG analysis, paving the way for advancements in early diagnosis and treatment strategies.…”
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Bio inspired optimization techniques for disease detection in deep learning systems by A. Ashwini, Vanajaroselin Chirchi, S. Balasubramaniam, Mohd Asif Shah

“…Abstract Numerous contemporary computer-aided disease detection methodologies predominantly depend on feature engineering techniques; yet, they possess several drawbacks, including the presence of redundant features and excessive time consumption. …”
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Development of data driven models to accurately estimate density of fatty acid ethyl esters by Walid Abdelfattah, Munthar Kadhim Abosaoda, Hardik Doshi, H. S. Shreenidhi, Manoranjan Parhi, Devendra Singh, Prabhjot Singh, Abdolali Yarahmadi Kandahari

“…Through extensive statistical evaluations and visualization techniques, SVR emerged as the most accurate model for density prediction. Sensitivity analysis confirms the influence of all input features, with SHAP analysis identifying temperature as the most dominant factor affecting density. …”
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Multi-view adversarial attack defending method for host intrusion detection by WANG Fei, QIAN Kehan, LYU Mingqi, ZHU Tiantian, CHEN Honglong

“…Host-based intrusion detection (HID) aims to identify attack behaviors through the analysis of host logs. …”
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SDFA-Net: Synergistic Dynamic Fusion Architecture With Deformable Attention for UAV Small Target Detection by Yunsong Qi, Hengwei Cao

“…Address the problem of leakage and misjudgment in small-target detection in aerial images. At the network architecture level, first, a lightweight multiscale attention feature extraction architecture is designed to improve the base module by introducing a heavily parameterized convolution and incorporating a multiscale attention mechanism. …”
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Quantitatively exploring the influence of geographical conditions on ecological quality using a novel remote sensing model: a comparison between two geographical disparity regions... by Hanqiu Xu, Mengjing Lin, Yifan Wang, Huade Guan, Fei Tang

“…This study applied the novel Remote Sensing-based Ecological Index (RSEI) concurrently to two distinct provincial-level regions in China, Fujian and Ningxia, to quantitatively detect their ecological differences. These two regions possess contrasting geographical conditions, with Fujian having high forest coverage and abundant rainfall, while Ningxia features low forest coverage and extensive loess plateau and desert terrain. …”
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ANALYZING EEG SIGNALS FOR STRESS DETECTION USING RANDOM FOREST ALGORITHM by Fi Imanur Sifaunnufus Ms, Fitra Abdurrachman Bachtiar, Barlian Henryranu Prasetio

“…The result of PSD is the power of each frequency of the EEG signal. The number of features used is 20. Random Forest was chosen due to its high accuracy and robustness in handling complex, high-dimensional data, which is common in EEG analysis. …”
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Potato Plant Leaf Disease Detection Using Deep Learning Method by Cemal İhsan Sofuoğlu, Derya Bırant

“…Improvements in the automated disease detection and analysis areas may provide important benefits for early action that would allow intervention at earlier stages for cure and preventing spread of the disease. …”
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A Driver’s Calling Behavior Detection Method Based on Deep Learning by XIONG Qunfang, LIN Jun, YUE Wei, LIU Shiwang, LUO Xiao, DING Chi

“…In order to prevent the driver from being distracted by the cell phone call, real-time monitoring of drivers’ behavior through video analysis is especially important. At present, driver’s calling behavior detection methods are prone to object occlusion, image rotation, illumination change and are difficult to extract deep features of the image, which degrade the detection accuracy. …”
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