An improved ViT model for music genre classification based on mel spectrogram. by Pingping Wu, Weijie Gao, Yitao Chen, Fangfang Xu, Yanzhe Ji, Juan Tu, Han Lin

“…In this paper, an improved ViT model is proposed to extract more comprehensive music genre features from Mel spectrograms by leveraging the strengths of both convolutional neural networks and Transformers. Also, the paper incorporates a channel attention mechanism by amplifying differences between channels within the Mel spectrograms of individual music genres, thereby facilitating more precise classification. …”
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EHAFF-NET: Enhanced Hybrid Attention and Feature Fusion for Pedestrian ReID by Jun Yang, Yan Wang, Haizhen Xie, Jiayue Chen, Shulong Sun, Xiaolan Zhang

“…This study addresses the cross-scenario challenges in pedestrian re-identification for public safety, including perspective differences, lighting variations, occlusions, and vague feature expressions. …”
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UCrack-DA: A Multi-Scale Unsupervised Domain Adaptation Method for Surface Crack Segmentation by Fei Deng, Shaohui Yang, Bin Wang, Xiujun Dong, Siyuan Tian

“…Additionally, by integrating a Mix-Transformer encoder, a multi-scale dilated attention module, and a mixed convolutional attention decoder, we effectively solve the challenges of cross-domain data distribution differences and complex scene crack segmentation. …”
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Artificial intelligence-based CT-free quantitative thyroid SPECT for thyrotoxicosis: study protocol of a multicentre, prospective, non-inferiority study by Jae Hoon Moon, Ji Hye Kim, Soyeon Ahn, Dongkyu Oh, Hyun Gee Ryoo, Hyun Woo Chung, Sang-Geon Cho, Kyounghyoun Kwon, Young So, Won Woo Lee

“…The trial will continue until 152 completed datasets have been enrolled to assess whether the 95% (two-sided) lower confidence limit of the accuracy difference (CT-free SPECT accuracy—SPECT/CT accuracy) for Graves’ disease is greater than −0.1. …”
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A Cascaded Network With Coupled High-Low Frequency Features for Building Extraction by Xinyang Chen, Pengfeng Xiao, Xueliang Zhang, Dilxat Muhtar, Luhan Wang

“…Although some studies have considered the integration between both high- and low-frequency features, they overlook the suitability of different network depths for extracting different frequency features. …”
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Exploratory development of human–machine interaction strategies for post-stroke upper-limb rehabilitation by Kang Xia, Xue-Dong Chang, Chong-Shuai Liu, Yu-Hang Yan, Han Sun, Yi-Min Wang, Xin-Wei Wang

“…For robot-in-charge and therapist-in-charge strategy, the desired and measured angle-time curve present good correlation, with low phase difference, which serve the purpose of real-time control. …”
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Cross-Visual Style Change Detection for Remote Sensing Images via Representation Consistency Deep Supervised Learning by Jinjiang Wei, Kaimin Sun, Wenzhuo Li, Wangbin Li, Song Gao, Shunxia Miao, Yingjiao Tan, Wei Cui, Yu Duan

“…Change detection techniques, which extract different regions of interest from bi-temporal remote sensing images, play a crucial role in various fields such as environmental protection, damage assessment, and urban planning. …”
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Hybrid Machine Learning Model for Efficient Botnet Attack Detection in IoT Environment by Mudasir Ali, Mobeen Shahroz, Muhammad Faheem Mushtaq, Sultan Alfarhood, Mejdl Safran, Imran Ashraf

“…As the Internet of Things (IoT) technology is developing rapidly, many network devices have been subject to botnet attacks leading to substantial losses in different sectors. Botnets pose serious risks to network security and deep learning models have shown potential for efficiently identifying botnet activity from network traffic data. …”
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Multimodal sleep staging network based on obstructive sleep apnea by Jingxin Fan, Jingxin Fan, Jingxin Fan, Mingfu Zhao, Li Huang, Li Huang, Bin Tang, Bin Tang, Lurui Wang, Zhong He, Zhong He, Xiaoling Peng

“…Finally, multiple channel data are integrated to address the heterogeneity between different modalities effectively and alleviate the impact of OSA on sleep stages.ResultsWe evaluated MSDC-SSNet on three public datasets and our collection of PSG records of 17 OSA patients. …”
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Advancing arabic dialect detection with hybrid stacked transformer models by Hager Saleh, Hager Saleh, Hager Saleh, Abdulaziz AlMohimeed, Rasha Hassan, Mandour M. Ibrahim, Saeed Hamood Alsamhi, Moatamad Refaat Hassan, Sherif Mostafa

“…The stacking model compares various models, including long-short-term memory (LSTM), gated recurrent units (GRU), convolutional neural network (CNN), and two transformer models using different word embedding. …”
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The Effectiveness of Deep Learning in the Differential Diagnosis of Hemorrhagic Transformation and Contrast Accumulation After Endovascular Thrombectomy in Acute Ischemic Stroke Pa... by Mehmet Beyazal, Merve Solak, Murat Tören, Berkutay Asan, Esat Kaba, Fatma Beyazal Çeliker

“…These labeled images were trained with nine different models under a convolutional neural network (CNN) architecture using a large dataset, such as ImageNet. …”
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Hybrid-KANet: a hyperspectral remote sensing crop classification method based on the Kolmogorov–Arnold network by Weizhen Zhang, Zhihui Li, Tong Zhen

“…The ablation experiments demonstrate the advantages of RBF kernel function in modeling complex nonlinear relationships by systematically comparing the differences in classification performance and boundary modeling ability of different kernel functions, which improves the classification accuracy and spatial consistency. …”
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Leveraging data analytics for detection and impact evaluation of fake news and deepfakes in social networks by Tony Mathew Abraham, Tao Wen, Ting Wu, Yu-wang Chen

“…This paper begins with a review of the literature on the definitions of fake news and deepfakes, their different types and major differences, and the ways they spread. …”
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Use of Vision Transformer to Classify Sea Surface Phenomena in SAR Imagery by Junfei Xia, Roland Romeiser, Wei Zhang, Tamay Ozgokmen

“…In addition, our study is the first to apply a pretrained ViT model to a dataset with different polarizations and spatial resolutions—the AI4Arctic Sea Ice Challenge dataset—to rigorously assess model adaptability. …”
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Multilevel Feature Cross-Fusion-Based High-Resolution Remote Sensing Wetland Landscape Classification and Landscape Pattern Evolution Analysis by Sijia Sun, Biao Wang, Zhenghao Jiang, Ziyan Li, Sheng Xu, Chengrong Pan, Jun Qin, Yanlan Wu, Peng Zhang

“…To address these issues, this study proposes the multilevel feature cross-fusion wetland landscape classification network (MFCFNet), which combines the global modeling capability of Swin Transformer with the local detail-capturing ability of convolutional neural networks (CNNs), facilitating discerning intraclass consistency and interclass differences. …”
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AttenCRF-U: Joint Detection of Sleep-Disordered Breathing and Leg Movements in OSA Patients by Qiuyue Li, Kewei Li, Cong Fu, Yiyuan Zhang, Huan Yu, Chen Chen, Wei Chen

“…Traditional single-event detection methods often overlook the dynamic interactions between SDB and LM, failing to capture their temporal overlap and differences in duration. To address this, we propose Attention-enhanced CRF with U-Net (AttenCRF-U), a novel joint detection framework that integrates multi-head self-attention (MHSA) within an encoder–decoder architecture to model long-range dependencies between overlapping events and employs multi-scale convolutional encoding to extract discriminative features across different temporal scales. …”
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DGCFNet: Dual Global Context Fusion Network for remote sensing image semantic segmentation by Yuan Liao, Tongchi Zhou, Lu Li, Jinming Li, Jiuhao Shen, Askar Hamdulla

“…The semantic segmentation task of remote sensing images often faces various challenges such as complex backgrounds, high inter-class similarity, and significant differences in intra-class visual attributes. Therefore, segmentation models need to capture both rich local information and long-distance contextual information to overcome these challenges. …”
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Automated note annotation after bioacoustic classification: Unsupervised clustering of extracted acoustic features improves detection of a cryptic owl by Callan Alexander, Robert Clemens, Paul Roe, Susan Fuller

“…Adaptation of these methods to other species and vocalisations may facilitate improved detection and investigation of vocal characteristics across different populations or regions.…”
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A Comparative Study of Lesion-Centered and Severity-Based Approaches to Diabetic Retinopathy Classification: Improving Interpretability and Performance by Gang-Min Park, Ji-Hoon Moon, Ho-Gil Jung

“…Third, we analyze how various model architectures and classification strategies perform under different labeling schemes. Finally, we evaluate decision-making differences between labeling methods using visualization techniques. …”
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Multiphysics property prediction from hyperspectral drill core data by A. V. Kamath, S. T. Thiele, M. Kirsch, R. Gloaguen

“…Our results show that, with careful preprocessing and thorough data cleaning, differences in resolution can be overcome to learn the relationship between hyperspectral data and petrophysics. …”
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