RDAU-Net: A U-Shaped Semantic Segmentation Network for Buildings near Rivers and Lakes Based on a Fusion Approach by Yipeng Wang, Dongmei Wang, Teng Xu, Yifan Shi, Wenguang Liang, Yihong Wang, George P. Petropoulos, Yansong Bao

“…The specular reflection of the water and boats with similar features to the buildings in the environment can greatly affect the performance of the algorithm. …”
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YOLO-DKM: A Flame and Spark Detection Algorithm Based on Deep Learning by Linpo Shang, Xufei Hu, Zijian Huang, Qiang Zhang, Zhiyu Zhang, Xin Li, Yanzuo Chang

“…And integrate DSConv into the C2f module, relying on dynamic characteristics to adaptively adjust convolution operations according to different scene features for more flexible local region feature extraction, capturing local features of flames and sparks. …”
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Unified Visual-Aware Representations for Data Analytics by Ladislav Peska, Ivana Sixtova, David Hoksza, David Bernhauer, Jakub Lokoc, Tomas Skopal

“…The desired property of the visualizations is the ability to visually encode the semantic features of the original data. Hence, processing of visualizations (images) by generic deep learning models results in deep feature vectors that could be uniformly used in standard data retrieval/analytics tasks. …”
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LOW COEFFICIENT CAUSES AND MECHANISMS OF USING OXYGEN IN HUMAN LUNGS IN THE FAR NORTH by B. T. Velichkovsky

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Sensitivity Analysis and Optimization of Urban Roundabout Road Design Parameters Based on CFD by Hangyu Zhang, Sihui Dong, Shiqun Li, Shuai Zheng

“…The pressure changes in the two feature points at the entrance conflict area and the inner ring weaving area are significantly correlated with the lane number parameters. …”
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基于峭度和小波包能量特征的齿轮箱早期故障诊断及抗噪研究 by 陈水宣, 邹俊, 易际明, 谢丹

“…It is difficult to dectect the gear fault signal in early stage because of weak intensity and strong interference.To solve this problem,a method for incipient fault diagnosis of gears is proposed based on vibration signals using kurtosis,wavelet packet energy features extraction and discriminative weighted probabilistic neural networks.The method uses the advantages of the kurtosis statistics on the impact load feature extraction method in feature extraction and reserves the merit of wavelet packet decomposition in extracting energy characteristics of various frequency bands.Meanwhile,the discriminative weight probabilistic neural network（DWPNN） is introduced to solve the problem of the scene noise pollution.The experimental results show that the method achieves a good identification of incipient faults of gears and has strong robustness against noise disturbance.…”
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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

“…Facing the problem of satellite navigation spoofing interference detection, a satellite navigation spoofing interference detection method based on LSTM was proposed. …”
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Phylogenetic analysis of a 2024 Sheeppox virus isolate from the Almaty region of Kazakhstan and investigation of its pathogenicity in merino sheep by Moldir Azanbekova, Muratbay Mambetaliyev, Aisulu Valiyeva, Nurlan Kozhabergenov, Nurbek Aldayarov, Sanat Kilibayev, Bekbolat Usserbayev, Moldir Tuyskanova, Balziya Kadyrova, Balzhan Myrzakhmetova, Lespek Kutumbetov, Olga Chervyakova, Sergazy Nurabayev, Maxat Berdikulov, Aslan Kerimbayev, Aralbek Rsaliyev, Yergali Abduraimov, Kuandyk Zhugunissov

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Prediction of Alzheimer’s Disease Based on Multi-Modal Domain Adaptation by Binbin Fu, Changsong Shen, Shuzu Liao, Fangxiang Wu, Bo Liao

“…Specifically, MM-DDA comprises three primary modules: (1) the feature encoding module, which employs convolutional neural networks (CNNs) to capture detailed and abstract feature representations from MRI and PET images; (2) the multi-head attention feature fusion module, which is used to fuse MRI and PET features, that is, to capture rich semantic information between modes from multiple angles by dynamically adjusting weights, so as to achieve more flexible and efficient feature fusion; and (3) the domain transfer module, which reduces the distributional discrepancies between the source and target domains by employing adversarial learning training. …”
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An efficient bearing fault detection strategy based on a hybrid machine learning technique by Khalid Alqunun, Mohammed Bachir Bechiri, Mohamed Naoui, Abderrahmane Khechekhouche, Ismail Marouani, Tawfik Guesmi, Badr M. Alshammari, Amer AlGhadhban, Abderrahim Allal

“…Abstract This study introduces an innovative method for addressing the bearing fault detection problem in rotating machinery. The proposed approach integrates multi-feature extraction, advanced feature selection, and state-of-the-art classification techniques using convolutional neural network (CNN) models. …”
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Improving medical image classification based on Boosted Beluga Whale Optimizer with Triangular Mutation and Cross Vision transformer models by Abdelghani Dahou, Mohamed Abd Elaziz, Ahmad O. Aseeri, Ahmed A. Ewees, Mohammed A.A. Al-qaness, Rehab Ali Ibrahim

“…In this study, we introduce a framework for medical image classification that combines deep learning models with modified Beluga Whale Optimization as a feature selection technique. Our approach utilizes a feature extraction technique called CrossViT, a vision transformer model architecture design of ViT. …”
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Deep learning-based automatic detection and grading of disk herniation in lumbar magnetic resonance images by Yan Guo, Xiaoxiang Huang, Wei Chen, Ichiro Nakamoto, Weiqing Zhuang, Hua Chen, Jie Feng, Jianfeng Wu

“…To address the difficulty of intervertebral disc feature extraction, the GS module was introduced into the backbone network, which enhances the feature learning ability for the key structures through the gradient splitting strategy, and the number of parameters was reduced by 2.1%. …”
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PAtt-Lite: Lightweight Patch and Attention MobileNet for Challenging Facial Expression Recognition by Jia Le Ngwe, Kian Ming Lim, Chin Poo Lee, Thian Song Ong, Ali Alqahtani

“…Facial Expression Recognition (FER) is a machine learning problem that deals with recognizing human facial expressions. …”
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DINOV2-FCS: a model for fruit leaf disease classification and severity prediction by Chunhui Bai, Chunhui Bai, Chunhui Bai, Lilian Zhang, Lilian Zhang, Lilian Zhang, Lutao Gao, Lutao Gao, Lutao Gao, Lin Peng, Lin Peng, Lin Peng, Peishan Li, Peishan Li, Peishan Li, Linnan Yang, Linnan Yang, Linnan Yang

“…In fruit leaf disease classification, for the problem that leaf spots of different diseases have great similarity, we have proposed Class-Patch Feature Fusion Module (C-PFFM), which integrates the local detailed feature information of the spots and the global feature information of the class markers. …”
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Video-Based Sign Language Recognition via ResNet and LSTM Network by Jiayu Huang, Varin Chouvatut

“…As the number of network layers increases, the ResNet network can effectively solve the granularity explosion problem and obtain better time series features. We use the ResNet convolutional network as the backbone model. …”
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RL-Net: a rapid and lightweight network for detecting tiny vehicle targets in remote sensing images by Yaoyao Du, Li Chen, Xingxing Hao

“…First, MobileNetV4 is introduced to optimize initial feature extraction, significantly improving the network’s efficiency. …”
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RMFKAN: Network Spammers Detection Method Based on Improved Graph Mamba by WANG Yuzhe, YAN Jinghua, BU Fanliang, WANG Yifan, LI Jia, HAN Zhuxuan

“…The method of heterogeneous perception long-distance relationship feature extraction is used to solve the problem of feature loss in long-distance relationships across communities in large-scale social networks. …”
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Addressing cross-population domain shift in chest X-ray classification through supervised adversarial domain adaptation by Aminu Musa, Rajesh Prasad, Monica Hernandez

“…Adversarial training fine-tunes the feature extractor, making features from both domains indistinguishable, thereby creating domain-invariant features. …”
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Forecasting formation density from well logging data based on machine learning model by Xiankang Cheng, Haoyu Zhang, Haoyu Zhang

“…A system structure integrating Convolutional neural network (CNN) and Transformer is suggested to accomplish the goal of automatic formation density prediction and solve the problem of insufficient model feature extraction ability under multiple logging data conditions. …”
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MFA-net: Object detection for complex X-ray cargo and baggage security imagery. by Thanaporn Viriyasaranon, Seung-Hoon Chae, Jang-Hwan Choi

“…Second, the fusion feature pyramid network combines the proposed attention and fusion modules to enhance multiscale object recognition and alleviate the object and occlusion problem. …”
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