Ensemble-based eye disease detection system utilizing fundus and vascular structures by Hongjie Yu, Xingbo Dong

“…Traditional diagnostic methods, relying on manually analyzing images, often have problems making an early detection and with their accuracy and efficiency, largely due to the subjectivity of human judgment and the time-consuming nature of the process. …”
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Detection Of Fire-Prone Areas In Attica Region Integrating Urban And Transport Aspect by Efthymia Kourmpa, Stefanos Tsigdinos

“…In Mediterranean climate areas, wildfires are one of the most critical problems bringing about several negative impacts (loss of human life, infrastructure damages, landscape transformation, natural environment deterioration, etc.). …”
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Tongue Color Analysis and Diseases Detection Based on a Computer Vision System by Abdulghafor Khudhaer Abdullah, Saleem Lateef Mohammed, Ali Al-Naji, Mohammed Sameer Alsabah

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Predicting learners' engagement and help-seeking behaviors in an e-learning environment by using facial and head pose features by Guan-Yun Wang, Yasuhiro Hatori, Yoshiyuki Sato, Chia-Huei Tseng, Satoshi Shioiri

“…The current study succeeded in estimating when participants are engaging in solving a problem and when they need help. Features obtained from facial videos are useful in improving e-learning education.…”
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18F-FDG PET and combined diffusion weighted MRI features in pleural infection: A case report by KyungAh Chun, MD, PhD

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Smart contract vulnerability detection method based on Bi-modal cross-attention mechanism by CHEN Jinfu, HU Xinyi, CAI Saihua, MIN Xirun

“…To address the problem that existing deep learning methods for smart contract vulnerability detection rely on single-modal feature extraction and insufficient contextual information capture, leading to relatively low detection accuracy, a smart contract vulnerability detection method based on the Bi-modal cross-attention mechanism was proposed. …”
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Clinical and psychological aspects of pregnancy and features of the course of labor in women with different types of psychological component of gestational dominant by V. M. Astakhov, O. V. Batsylieva, I. V. Puz

“…The results obtained indicate the need to organize a comprehensive medical and psychological support for pregnant women, during which a diagnosis of the psycho-emotional state in pregnant women with the detection of PCGD type is binding. This approach would not only help to prevent a number of clinical and psychological problems that may occur in women during pregnancy, but also to allow for the harmonious growth of an intrauterine fetus, effective women’s adaptation to the situation of impending motherhood and the birth of a healthy child.…”
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基于透视不变二值特征描述子的图像匹配算法 by Li-chuan GENG, Song-zhi SU, Shao-zi LI

“…Current local feature based image matching algorithms are usually less robust to image perspective transformation.Aiming to solve this problem，a new perspective invariant binary code (PIBC) based image matching algorithm is proposed.Firstly，FAST corners are detected on the pyramid images，those corners with non-maximum Harris corner response value and the edge points are further eliminated.And then，by simulating the perspective transformations of images taken from different viewpoints，a single FAST corner is described with binary descriptors under different viewpoint transformations，which makes the descriptor could describe the identical feature point on different perspective transform images.Experimental results show its robustness to image perspective transformation，while its complexity is similar with SURF.…”
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基于透视不变二值特征描述子的图像匹配算法 by Li-chuan GENG, Song-zhi SU, Shao-zi LI

“…Current local feature based image matching algorithms are usually less robust to image perspective transformation.Aiming to solve this problem，a new perspective invariant binary code (PIBC) based image matching algorithm is proposed.Firstly，FAST corners are detected on the pyramid images，those corners with non-maximum Harris corner response value and the edge points are further eliminated.And then，by simulating the perspective transformations of images taken from different viewpoints，a single FAST corner is described with binary descriptors under different viewpoint transformations，which makes the descriptor could describe the identical feature point on different perspective transform images.Experimental results show its robustness to image perspective transformation，while its complexity is similar with SURF.…”
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Hematological features of mine-blast trauma, accompanied by acubarotrauma, among servicemen - participants in high-intensity combat operations by S. A. Husieva, G. V. Osyodlo, I. P. Goncharov, O. Ya. Antonyuk, Yu. Ya. Kotyk, A. V. Gusev, М. Е. Krol, I. V. Malysh, Ya. M. Klimenko, S. V. Ткаchenko

“…A feature of the peripheral blood of patients with ear injury was a significant increase (p<0,05) in the absolute number of monocytes (0.7±0.36×10⁹/l) compared to the results of the control group (0.29±0.11×10⁹/l). …”
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Research on the detection of obstacles in front of unmanned vehicles in opencast mines based on binocular vision by Shunling RUAN, Huiguo ZHANG, Qinghua GU, Caiwu LU, Di LIU, Jing MAO

“…The Feffol network model proposed in this paper selects Efficient-v2 as the backbone network structure for feature extraction in the feature extraction stage, selects the Ebifpn feature pyramid module based on the SppCSP structure with SppCSP structure to improve the feature sensing field while enhancing the feature information of different sizes, uses the Focal Loss and CIoU Loss loss functions to balance positive and negative samples, and solve the problem of method failure when there is no intersection between the prediction frame and the real detection frame. …”
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Res-SE-ConvNet: A Deep Neural Network for Hypoxemia Severity Prediction for Hospital In-Patients Using Photoplethysmograph Signal by Talha Ibn Mahmud, Sheikh Asif Imran, Celia Shahnaz

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GDSN-CD: Graph-Guided Diffusion Synergistic Network for Remote Sensing Change Detection by Yunfei Zhu, Jintao Song, Jinjiang Li

“…Remote sensing change detection often faces the challenge of accurately capturing discontinuous change features in complex scenes. …”
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Blind Infrared Remote-Sensing Image Deblurring Algorithm via Edge Composite-Gradient Feature Prior and Detail Maintenance by Xiaohang Zhao, Mingxuan Li, Ting Nie, Chengshan Han, Liang Huang

“…To address this challenge, traditional methods often rely on sparse regularization priors to mitigate the uncertainty inherent in the problem. In this paper, we propose a novel blind deblurring model based on the MAP framework that leverages Composite-Gradient Feature (CGF) variations in edge regions after image blurring. …”
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LI-YOLO: An Object Detection Algorithm for UAV Aerial Images in Low-Illumination Scenes by Songwen Liu, Hao He, Zhichao Zhang, Yatong Zhou

“…In the feature fusion part, aiming to improve the detection performance for small objects in UAV aerial images, a shallow feature fusion network and a small object detection head are added. …”
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A Tank Experiment of the Autonomous Detection of Seabed-Contacting Segments for Submarine Pipelaying Operations by Bo Wang, Jie Wang, Chen Zheng, Ye Li, Jian Cao, Yueming Li

“…Due to the weak structural features of pipelines and underwater light attenuation, the complex and harsh environment of the seabed greatly increases the possibility of an underwater autonomous remotely operated vehicle losing a detected seabed-contacting segment during pipe-laying operations. …”
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Abnormal traffic detection method based on LSTM and improved residual neural network optimization by Wengang MA, Yadong ZHANG, Jin GUO

“…Problems such as a difficulty in feature selection and poor generalization ability were prone to occur when traditional method was exploited to detect abnormal network traffic.Therefore, an abnormal traffic detection method based on the long short term memory network (LSTM) and improved residual neural network optimization was proposed.Firstly, the features and attributes of network traffic were analyzed, and the variability of the feature values was reduced by preprocessing of network traffic.Then, a three-layer stacked LSTM network was designed to extract network traffic features of different depths.Moreover, the problem of weak adaptability of feature extraction was solved.Finally, an improved residual neural network with skipping connecting line was designed to optimize the LSTM.The defects of deep neural network such as overfitting and gradient vanishing were optimized.The accuracy of abnormal traffic detection was improved.Experimental results show that the proposed method has higher training accuracy and better visibility of data processing.The classification accuracy rates under two classifications and multiple classifications are 92.3% and 89.3%.It has the lowest false positive rate when the parameters such as precision rate and recall rate are optimal.Moreover, it has strong robustness when the sample is destroyed.Furthermore, better generalization ability can be achieved.…”
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Abnormal events detection using spatio-temporal saliency descriptor and fuzzy representation analysis by R. Tino Merlin, R. Karthick, A. Aalan Babu, G. Vennira Selvi, D. Usha, R. Nithya

“…Moreover, many feature representations have limited capability to describe the content since several research works applied hand craft features, this type of feature can work in limited problems. …”
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Depression detection based on dual path DCGAN data generation and classification-regression network by LU Jingxue, LI Hongyan, ZHENG Ruichao, QIN Ruizhen

“…The existing research on voice-based depression detection has many problems, such as complicated feature extraction, single data expansion and uncontrollable prediction bias in regression prediction. …”
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RGB-D Image Saliency Detection Based on Multi-branch Backbone Supervised Network by WANG Wei-bing, ZHANG Xiao-zhuo, DENG Qiang

“…Aiming at the problem that the existing RGB-D image saliency detection technology is difficult to fully explore the effective information of depth image and can not effectively integrate RGB features and deep features, an RGB-D image saliency detection method under multi-branch backbone supervision network is proposed. …”
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