BANet: A bilateral attention network for extracting changed buildings between remote sensing imagery and cadastral maps by Qingyu Li, Lichao Mou, Yilei Shi, Xiao Xiang Zhu

“…This confirms that the leverage of bilateral attention blocks (BAB) can boost performance.…”
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Integrated WHT- and DFT-Based Multiuser Massive MIMO System for Secure RIS-Enabled mmWave Communications by Md. Najmul Hossain, Md. Rakibul Islam, S. K. Tamanna Kamal, Atia Kaniz, Shaikh Enayet Ullah, Tetsuya Shimamura

“…The system integrates a two-dimensional (2D) hyperchaotic system for physical layer security (PLS) encryption, block diagonalization (BD) precoding, repeat-accumulate (RA) channel coding utilizing Cholesky decomposition-based zero-forcing (CD-ZF), and minimum mean square error (MMSE) signal detection techniques. …”
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Multi-keyword partial matching algorithm based on text fragments by LIAO Wei-qi, ZOU Wei

“…A novel multi-keyword partial matching algorithm was also de- signed and realized which could detect the fraction of keywords in data block without re-flow or re-file. …”
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Genome-Wide Association Study for Resistance to <i>Phytophthora sojae</i> in Soybean [<i>Glycine max</i> (L.) Merr.] by Hee Jin You, Ruihua Zhao, Yu-Mi Choi, In-Jeong Kang, Sungwoo Lee

“…These findings underscore the necessity for robust statistical models to accurately detect true marker–trait associations and provide valuable insights into soybean genetics and breeding.…”
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PyionNet: Pyramid Progressive Cross-Fusion Network for Joint Classification of Hyperspectral and LiDAR Data by Haizhu Pan, Quanxiu Zhang, Haimiao Ge, Moqi Liu, Cuiping Shi

“…Joint hyperspectral (HS) and light detection and ranging (LiDAR) data for land cover classification have received widespread attention. …”
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Real-time diagnosis of multi-category skin diseases based on IR-VGG by Ling TAN, Shanshan RONG, Jingming XIA, Sarker SAJIB, Wenjie MA

“…Malignant skin lesions have a very high cure rate in the early stage.In recent years, dermatological diagnosis research based on deep learning has been continuously promoted, with high diagnostic accuracy.However, computational resource consumption is huge and it relies on large computing equipment in hospitals.In order to realize rapid and accurate diagnosis of skin diseases on Internet of things (IoT) mobile devices, a real-time diagnosis system of multiple categories of skin diseases based on inverted residual visual geometry group (IR-VGG) was proposed.The contour detection algorithm was used to segment the lesion area of skin image.The convolutional block of the first layer of VGG16 was replaced with reverse residual block to reduce the network parameter weight and memory overhead.The original image and the segmented lesion image was inputed into IR-VGG network, and the dermatological diagnosis results after global and local feature extraction were outputed.The experimental results show that the IR-VGG network structure can achieve 94.71% and 85.28% accuracy in Skindata-1 and Skindata-2 skin diseases data sets respectively, and can effectively reduce complexity, making it easier for the diagnostic system to make real-time skin diseases diagnosis on IoT mobile devices.…”
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Lysozyme functionalized zinc-oxide nanoparticles: Synthesis, characterization, and antibacterial assessment against Staphylococcus aureus with futuristic application in wastewater... by Suneeti Singh, Pavni Rekhi, Jewel Mary Saju

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A robust deep learning framework for multiclass skin cancer classification by Burhanettin Ozdemir, Ishak Pacal

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Lightweight defocus deblurring network for curved-tunnel line scanning using wide-angle lenses by Shaojie Qin, Taiyue Qi, Xiaodong Huang, Xiao Liang

“…The proposed depthwise ResBlocks significantly improves the parameter efficiency of the network. …”
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Lightweight Deep Learning Model for Fire Classification in Tunnels by Shakhnoza Muksimova, Sabina Umirzakova, Jushkin Baltayev, Young-Im Cho

“…This model integrates MobileNetV3 for spatial feature extraction, Temporal Convolutional Networks (TCNs) for temporal sequence analysis, and advanced attention mechanisms, including Convolutional Block Attention Modules (CBAMs) and Squeeze-and-Excitation (SE) blocks, to prioritize critical features such as flames and smoke patterns while suppressing irrelevant noise. …”
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Kolmogorov&#x2013;Arnold&#x2013;Enhanced Nonlinear Expansions for Fine-Grained Feature Amplification in Robust Near-Shore SAR Vessel Discrimination by Hankang Wang, Gaopeng Huang, Zhao Huang, Xingru Huang, Zhaoyang Xu, Zhiwen Zheng, Shanwei Liu, Shiqing Wei, Jin Liu, Xiaoshuai Zhang

“…To address these issues, we propose Kolmogorov&#x2013;Arnold&#x2013;Enhanced YOLO (KaneYOLO), a novel SAR ship detector designed for robust discrimination in complex nearshore scenes and enhanced small-target detection. First, we introduce KAN Block, a feature extraction module leveraging the Kolmogorov&#x2013;Arnold theorem to model complex nonlinear relationships in SAR images. …”
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TomatoPoseNet: An Efficient Keypoint-Based 6D Pose Estimation Model for Non-Destructive Tomato Harvesting by Jipeng Ni, Licheng Zhu, Lizhong Dong, Ruixue Wang, Kaikang Chen, Jianbo Gao, Wenbei Wang, Liming Zhou, Bo Zhao, Jiacheng Rong, Zhenhao Han, Kunlei Lu, Xuguang Feng

“…Furthermore, simple coordinate classification (SimCC) is employed as the head network for keypoint detection, and a StripPooling block is introduced to enhance the model’s ability to capture features of different scales and shapes by applying strip pooling in horizontal and vertical directions. …”
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Progressive multi-scale attention neural network for pneumonia classification in chest X-rays by Mohammad Reza Mahdiani

“…Unlike previous methods that overlook fine-grained edge information or fail to integrate multi-scale contextual features, our approach synergistically combines convolutional multi-scale feature extraction using depthwise separable convolutions with cross-layer feature fusion, Transformer blocks, advanced attention mechanisms, and a custom loss function that emphasizes diagnostically relevant edge details using Canny edge detection. …”
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Deep Learning-Based Navigation System for Automatic Landing Approach of Fixed-Wing UAVs in GNSS-Denied Environments by Ying-Xi Lin, Ying-Chih Lai

“…However, GNSS signals can be blocked in specific environments and are susceptible to jamming and spoofing, which will degrade the performance of navigation systems. …”
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Application of UAV and satellite technologies for assessing phytophthora root rot severity in avocado orchards by S. Duncan, A. McLeod, C. Poblete-Echeverria

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A hybrid attention-based deep learning framework for precise early diagnosis of Alzheimer’s disease by Romoke Grace Akindele, Shixin Cen, Ming Yu, Ifeoluwapo Aribilola, Tian Xinrang, Yu Liu

“…However, accurate early detection remains challenging due to overlapping features across disease stages and the complexity of neuroimaging data. …”
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Peptide nucleic acid (PNA) clamps reduce amplification of host chloroplast and mitochondria rRNA gene sequences and increase detected diversity in 16S rRNA gene profiling analysis... by Usman Hussain, Jim Downie, Amy Ellison, Sandra Denman, James McDonald, Marine C. Cambon

“…Peptide Nucleic Acid (PNA) clamps prevent this by blocking PCR primer binding or binding within the amplified region of non-target DNA to stop the function of DNA polymerase. …”
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Feature extraction method based on point pair hierarchical clustering by Jiang Qian, Ruixin Zhao, Jingkang Wei, Xiaohui Luo, Yilan Xue

“…Conventional feature detection algorithms are largely based on clustered two-dimensional (2D) blocks of information. …”
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Connectivity and community structure of online and register-based social networks by Márton Menyhért, Eszter Bokányi, Rense Corten, Eelke M. Heemskerk, Yuliia Kazmina, Frank W. Takes

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Facial identity recognition using StyleGAN3 inversion and improved tiny YOLOv7 model by Akhil Kumar, Swarnava Bhattacharjee, Ambrish Kumar, Dushantha Nalin K. Jayakody

“…To perform facial attribute and identity detection, we developed the Spatial Transformer Block (STB) and Squeeze-Excite Spatial Pyramid Pooling (SE-SPP)-based Tiny YOLOv7 model and proposed as FIR-Tiny YOLOv7 (Facial Identity Recognition-Tiny YOLOv7) model. …”
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