Vision Transformers (ViTs) for Feature Extraction and Classification of AI-Generated Visual Designs by Qing Yun

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Coseismic Landslide Mapping Based on Trans-UNet and Transfer Learning by Tianhe Ren, Wenping Gong, Jun Chen, Liang Gao, Jiahao Wu, Xuyang Xiang

“…The Trans-UNet model integrates a UNet-like encoder–decoder structure with a Transformer module to enhance global context extraction, a U-shaped full-scale feature extraction module to preserve multiscale spatial details, and a convolutional decoder for effective feature fusion and resolution restoration. …”
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LCCDMamba: Visual State Space Model for Land Cover Change Detection of VHR Remote Sensing Images by Junqing Huang, Xiaochen Yuan, Chan-Tong Lam, Yapeng Wang, Min Xia

“…The proposed MISF comprises multi-scale feature aggregation (MSFA), which utilizes strip convolution to aggregate multiscale local change information of bitemporal land cover features, and residual with SS2D (RSS) which employs residual structure with SS2D to capture global feature differences of bitemporal land cover features. …”
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Single-Image Superresolution for RGB Remote Sensing Imagery via Multiscale CNN-Transformer Feature Fusion by Xudong Yao, Haopeng Zhang, Sizhe Wen, Zhenwei Shi, Zhiguo Jiang

“…MSTB generates multiscale tokens with multiple convolutional layers to obtain multiscale global information. …”
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An explainable hybrid feature aggregation network with residual inception positional encoding attention and EfficientNet for cassava leaf disease classification by M. Sundara Srivathsan, S. Alden Jenish, K. Arvindhan, R. Karthik

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A Lightweight Semantic- and Graph-Guided Network for Advanced Optical Remote Sensing Image Salient Object Detection by Jie Liu, Jinpeng He, Huaixin Chen, Ruoyu Yang, Ying Huang

“…The SggNet adopts a classical encoder-decoder structure with MobileNet-V2 as the backbone, ensuring optimal parameter utilization. …”
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Urban Land Use Classification Model Fusing Multimodal Deep Features by Yougui Ren, Zhiwei Xie, Shuaizhi Zhai

“…The spectral features and subgraph features are then constructed, and a graph convolutional network (GCN) is utilized to extract the node relational features from both the global and local graphs, forming the topological structure deep features while aggregating local features into global ones. …”
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Self-Supervised Social Recommendation Algorithm Fusing Residual Networks by WANG Yujie, YANG Zhe

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Residual Vision Transformer and Adaptive Fusion Autoencoders for Monocular Depth Estimation by Wei-Jong Yang, Chih-Chen Wu, Jar-Ferr Yang

“…In this paper, by using a single camera, we propose an end-to-end supervised monocular depth estimation autoencoder, which contains an encoder with a structure with a mixed convolution neural network and vision transformers and an effective adaptive fusion decoder to obtain high-precision depth maps. …”
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Quantifying Interdisciplinarity in Scientific Articles Using Deep Learning Toward a TRIZ-Based Framework for Cross-Disciplinary Innovation by Nicolas Douard, Ahmed Samet, George Giakos, Denis Cavallucci

“…Interdisciplinary research (IDR) is essential for addressing complex global challenges that surpass the capabilities of any single discipline. …”
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Advanced AI techniques for classifying Alzheimer’s disease and mild cognitive impairment by Sophie Tascedda, Sophie Tascedda, Sophie Tascedda, Pierfrancesco Sarti, Pierfrancesco Sarti, Veronica Rivi, Claudia Savia Guerrera, Giuseppe Alessio Platania, Mario Santagati, Filippo Caraci, Filippo Caraci, Johanna M. C. Blom, Johanna M. C. Blom

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Speckle Noise Reduction for Medical Ultrasound Images Using Hybrid CNN-Transformer Network by Anparasy Sivaanpu, Kumaradevan Punithakumar, Rui Zheng, Michelle Noga, Dean Ta, Edmond H. M. Lou, Lawrence H. Le

“…It is integrated into the encoder-decoder structure, allowing the model to focus on both local and global texture structural information. …”
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Graph-Based Feature Crossing to Enhance Recommender Systems by Congyu Cai, Hong Chen, Yunxuan Liu, Daoquan Chen, Xiuze Zhou, Yuanguo Lin

“…Additionally, ensuring that the crossed features capture both global graph structures and local context is non-trivial, requiring innovative techniques for multi-scale representation learning. …”
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ROPGCViT: A Novel Explainable Vision Transformer for Retinopathy of Prematurity Diagnosis by Mustafa Yurdakul, Kubra Uyar, Sakir Tasdemir, Irfan Atabas

“…GCViT was enhanced with Squeeze-and-Excitation (SE) block and Residual Multilayer Perceptron (RMLP) structures to effectively learn local and global context information. …”
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Detection of Diabetic Retinopathy Using a Multi-Decision Inception-ResNet-Blended Hybrid Model by Santosh Kumar Henge, Nikhil Reddy Viraati, Musaed Alhussein, Ajay Shriram Kushwaha, Khursheed Aurangzeb, Ravleen Singh

“…The model undergoes thorough pre-processing and testing phases, utilizing eight layers of convolutions at each stage to handle various data matrices and integrate global and specialized features. …”
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Using deep learning to screen OCTA images for hypertension to reduce the risk of serious complications by Yiheng Ding, Ziqiang Wei, Chaoyun Wang, Xinyue Li, Bingbing Li, Xueting Liu, Zhijie Fu, Hongwei Mo, Hong Zhang

“…BackgroundAs a disease with high global incidence, hypertension is known to cause systemic vasculopathy. …”
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NGSTGAN: N-Gram Swin Transformer and Multi-Attention U-Net Discriminator for Efficient Multi-Spectral Remote Sensing Image Super-Resolution by Chao Zhan, Chunyang Wang, Bibo Lu, Wei Yang, Xian Zhang, Gaige Wang

“…Recent advancements in convolutional neural networks (CNNs) and Transformers have significantly improved RSISR performance due to their capabilities in local feature extraction and global modeling. …”
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PolyBuild: An End-to-End Method for Polygonal Building Contour Extraction From High-Resolution Remote Sensing Images by Yaoteng Zhang, Julin Zhang, Guangshuai Wang, Jiwei Deng, Hui Sheng, Yasir Muhammad, Shiqing Wei

“…However, the presence of varying imaging conditions and complex building structures, makes automatic contour extraction extremely challenging. …”
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Multi-scale Information Aggregation for Spoofing Detection by Changtao Li, Yi Wan, Feiran Yang, Jun Yang

“…In this paper, we propose a spoofing detection system built on SincNet and Deep Layer Aggregation (DLA), which leverages speech representations at different levels to distinguish synthetic speech. DLA is totally convolutional with an iterative tree-like structure. …”
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Fine-grained crop pest classification based on multi-scale feature fusion and mixed attention mechanisms by Yiheng Qian, Zhiyong Xiao, Zhaohong Deng

“…Additionally, a Transformer block is integrated to overcome the limitations of traditional convolutional approaches in capturing global contextual information. …”
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