Hierarchical Structure Estimation of Financial Networks and Sentiment Analysis of Financial News Headlines by Naijia Liu, Kaira Sekiguchi, Yoshiyuki Nakata, Toshiaki Sugie, Takaaki Yoshino, Yukio Ohsawa

“…In this study, we apply the one-layer Hierarchical Stochastic Block Model (HSBM) to detect anomalies by analyzing market changes and the underlying spatial structure, providing crucial insights to support investors’ investment decisions. …”
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Yo3RL-Net:A fusion of two-phase end-to-end deep net framework for hand detection and gesture recognition by Xiang Wu, Yuanhao Ma, Shijie Zhang, Tianfei Chen, He Jiang

“…In order to tackle these problems, we suggest a sophisticated approach called Yo3RL-Net using Yolo Algorithm and 3D Resnet-LSTM, which is designed specifically for hand detection and gesture recognition. During the hand detection phase, the YOLOv8 algorithm is improved by incorporating dynamic snake convolutions, CPCA attention modules, and a detection layer specifically designed for small targets. …”
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CDSE-UNet: Enhancing COVID-19 CT Image Segmentation With Canny Edge Detection and Dual-Path SENet Feature Fusion by Jiao Ding, Jie Chang, Renrui Han, Li Yang

“…In response to blurred boundaries and high variability characteristic of lesion areas in COVID-19 CT images, we introduce CDSE-UNet: a novel UNet-based segmentation model that integrates Canny operator edge detection and a Dual-Path SENet Feature Fusion Block (DSBlock). …”
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Secure ISAC MIMO systems: exploiting interference with Bayesian Cramér–Rao bound optimization by Nanchi Su, Fan Liu, Christos Masouros, George C. Alexandropoulos, Yifeng Xiong, Qinyu Zhang

“…Our extensive numerical results verify the effectiveness of the proposed secure ISAC design showing that the proposed algorithm outperforms block-level precoding techniques.…”
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HiDRA-DCDNet: Dynamic Hierarchical Attention and Multi-Scale Context Fusion for Real-Time Remote Sensing Small-Target Detection by Jiale Wang, Zhe Bai, Ximing Zhang, Yuehong Qiu, Fan Bu, Yuancheng Shao

“…Small-target detection in remote sensing presents three fundamental challenges: limited pixel representation of targets, multi-angle imaging-induced appearance variance, and complex background interference. …”
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TLEABLCNN: Brain and Alzheimer’s Disease Detection Using Attention-Based Explainable Deep Learning and SMOTE Using Imbalanced Brain MRI by Erol Kina

“…This work presents a lightweight convolutional architecture based on EfficientNet with a Squeeze Attention Block using transfer learning. The proposed approach used lightweight layers with an L2 regularizer, global pooling (2D), and batch normalisation to construct the model, including two dropout layers. …”
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StApneaNet: A Deep Learning-Based Automatic Sleep Stage Adaptive Apnea Detection Network Using Single Channel EEG Signal by Suvasish Saha, Shaikh Anowarul Fattah, Mohammad Saquib

“…A residual squeeze and excitation based channel attention mechanism is then applied to the output feature channels which are further processed through a bi-directional long short term memory (Bi-LSTM) layer along with a temporal attention block. Both apnea prediction and sleep stage prediction are jointly optimized in the joint model that is initially pre-trained and later integrated as a non-trainable block with the trainable decision fusion block inside the decision model for the final apnea event detection. …”
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Multi-scale target intelligent detection method for coal, foreign object and early damage of conveyor belt surface under low illumination and dust fog by Hongwei FAN, Jinpeng LIU, Xiangang CAO, Chao ZHANG, Xuhui ZHANG, Man LI, Hongwei MA, Qinghua MAO

“…Then, by adding a shallow detection layer to highlight the detailed information such as the position and shape of the small target of the early belt surface damage, the performance of the early belt surface damage detection is improved, in the meantime some detection layers and corresponding feature extraction modules are removed to reduce the model without affecting the detection accuracy. …”
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Tunnel Lining Recognition and Thickness Estimation via Optical Image to Radar Image Transfer Learning by Chuan Li, Tong Pu, Nianbiao Cai, Xi Yang, Hao Liu, Lulu Wang

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An airport apron ground service surveillance algorithm based on improved YOLO network by Yaxi Xu, Yi Liu, Ke Shi, Xin Wang, Yi Li, Jizong Chen

“…This research shows an activity identification algorithm for ground service objects in an airport apron area and proposes an improved YOLOv5 algorithm to increase the precision of small object detection by introducing an SPD-Conv (spath-to-depth-Conv) block in YOLOv5's backbone layer. …”
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Efficient Side-Tuning for Remote Sensing: A Low-Memory Fine-Tuning Framework by Haichen Yu, Wenxin Yin, Hanbo Bi, Chongyang Li, Yingchao Feng, Wenhui Diao, Xian Sun

“…EST attaches a parallel network to the backbone of the model, and only fine-tunes the parameters of the parallel network during the training phase. The proposed EST Block is the main component of the parallel network, which uses the multichannel adapter fusion module, gate layer and depthwise convolution to achieve feature selection and enhancement effects. …”
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Rapid Discrimination of Aging Year of Chenpi Based on Hyperspectral Images by Cheng LIU, Lulu ZHAO, Songbin ZHOU, Yisen LIU, Tingyou WANG

“…This approach evaluated the importance of spectral bands across multiple Rep-block layers, indicating band significance while considering inter-band and remote correlations. …”
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scSEETV‐Net: Spatial and Channel Squeeze‐Excitation and Edge Attention Guidance V‐Shaped Network for Skin Lesion Segmentation by Hakan Ocal

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UAV-based estimation of post-sowing rice plant density using RGB imagery and deep learning across multiple altitudes by Trong Hieu Luu, Thanh Tam Nguyen, Quang Hieu Ngo, Huu Cuong Nguyen, Phan Nguyen Ky Phuc

“…The robust rice plant density estimation process incorporates two key innovations: first, a dynamic system of 12 adaptive segmentation thresholding blocks that effectively detects rice seed presence across diverse and variable background conditions. …”
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Transceiver Design of a Secure Multiuser FDSS-Based DFT-Spread OFDM System for RIS- and UAV-Assisted THz Communications by Md. Najmul Hossain, Kottakkaran Sooppy Nisar, Tetsuya Shimamura, Md. Rakibul Islam, Sk. Tamanna Kamal, Shaikh Enayet Ullah

“…In addition, the block diagonalization (BD) precoding technique reduces multiuser interference (MUI). …”
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Principal Component Analysis-Multilinear Perceptron-based model for Distributed Denial of Service Attack Mitigation by Opeyemi Oreoluwa Asaolu, Oluwasanmi Segun Adanigbo, Afeez Adekunle Soladoye, Nnamdi Stephen Okomba

“…In this study, a PCA-MLP (Principal Component Analysis-Multi-Layer Perceptron) intrusion detection model combined with a packet-filtering firewall for enhanced prevention is presented. …”
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CENTRAL ASIAN GEODYNAMIC REGIMES WEST AND EAST 102–104° GEODIVIDER by Yu. G. Gatinsky, T. V. Prokhorova, D. V. Rundquist

“…Near the geodivider, a seismic energy increase is detected east of it only at the western border of the South-Eastern China Block. …”
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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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Optimal features assisted multi-attention fusion for robust fire recognition in adverse conditions by Inam Ullah, Nada Alzaben, Yousef Ibrahim Daradkeh, Mi Young Lee

“…Abstract Deep neural networks have significantly enhanced visual data-based fire detection systems. However, high false alarm rates, shallow-layered networks, and poor recognition in challenging environments continue to hinder their practical deployment. …”
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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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