Airport-FOD3S: A Three-Stage Detection-Driven Framework for Realistic Foreign Object Debris Synthesis by Hanglin Cheng, Yihao Li, Ruiheng Zhang, Weiguang Zhang

“…Additionally, a three-stage image blending method considering size transformation, a seamless process, and style transfer was proposed. …”
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Efficacy of neoadjuvant, adjuvant, and perioperative immunotherapy in non-small cell lung cancer across different PD-L1 expression levels: a systematic review and meta-analysis by Zhenlong Zhang, Zhenlong Zhang, Yuchen Lin, Shuchen Chen

“…BackgroundImmune checkpoint inhibitors, particularly anti-PD-1/PD-L1 monoclonal antibodies, have transformed non-small cell lung cancer (NSCLC) treatment. …”
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Similarities and differences of a proliferation-inducing ligand expression in lacrimal gland lesions of patients with IgG4-associated ophthalmic diseases and mucosa-associated lymp... by Lvfu He, Lvfu He, Lisha Zhan, Yu Yang, Weimin He

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Multi-label Classification Based on Label-Aware Variational Autoencoder by SUN Hongjian, XU Pengyu, LIU Bing, JING Liping, YU Jian

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Fusion of Recurrence Plots and Gramian Angular Fields with Bayesian Optimization for Enhanced Time-Series Classification by Maria Mariani, Prince Appiah, Osei Tweneboah

“…To ensure optimal performance, Bayesian Optimization is employed to automatically select the ideal image resolution, eliminating the need for manual tuning. Unlike prior methods that rely on individual transformations, our approach concatenates RP, GASF, and GADF into a unified representation and generalizes to multivariate data by stacking transformation channels across sensor dimensions. …”
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Effects of Alprostadil on experimental peritoneal fibrosis in rats by ZHANG Yan-min, CHEN Wei-dong, WAN Sheng, CHEN Dan, CHEN Fang, DING Yan-qiong, WANG Zeng-si, TIAN Hong-dan, XIONG Fei

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Offline reinforcement learning combining generalized advantage estimation and modality decomposition interaction by Kaixin Jin, Lifang Wang, Xiwen Wang, Wei Guo, Qiang Han, Xiaoqing Yu

“…However, existing Transformer-based methods face limitations, such as ineffective trajectory stitching and the neglect of deep interactions within and between multimodal information in trajectories. …”
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DCAI: a dual cross-attention integration framework for benign-malignant classification of pulmonary nodules by Shuling Wang, Suixue Wang, Rongdao Sun

“…These features are encoded using Transformer models, and then a dual cross-attention module is proposed to dynamically align and interact with the complementary information between the different modalities. …”
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Crop field extraction from high resolution remote sensing images based on semantic edges and spatial structure map by Liegang Xia, Ruiyan Liu, Yishao Su, Shulin Mi, Dezhi Yang, Jun Chen, Zhanfeng Shen

“…This method relies on good connectivity to repair fragmented edges that may appear in semantic edge detection. …”
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MCGFE-CR: Cloud Removal With Multiscale Context-Guided Feature Enhancement Network by Qiang Bie, Xiaojie Su

“…The experimental results demonstrate that this method has higher spectral fidelity and richer structural texture information in reconstructing various types of ground information and optical images with different cloud coverage areas.…”
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BLTTNet: feature fusion based on BiLSTM-Transfomer-TCN for prediction of remaining useful life of aircraft engines by Yixu Yang, Xiaoying Su, Chaoyong Wang, Hongxi Liu, Kunhao Fu, Tao Xie, Zishuo Zhang

“…Specifically, DCEFormer with a Transformer structure enhances the allocation of feature weights by processing the contributions of different features in both the time step dimension and the sensor dimension, thereby improving the accuracy of RUL prediction for mechanical equipment. …”
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Enhancing the quality of low-light images via the coefficient bounds derived for a subclass of Sakaguchi-type function by K. Sivagami Sundari, B. Srutha Keerthi

“…Abstract This paper introduces a new approach for enhancing low-light images by utilizing coefficient bounds from a specific subclass of analytic functions, a concept rooted in geometric function theory. Our method is designed to adapt dynamically to different lighting conditions, ensuring effective image enhancement in both uniformly and non-uniformly illuminated environments. …”
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NMT-translation – basic models, quality assessment by I. A. Borunov

“…In order to achieve this goal, the following tasks were formulated: to review and analyze the main NMT models, including Seq2Seq, Transformer, BERT and their variations, in order to identify their peculiarities and applicability to the translation of different types of texts; to study and evaluate the quality of translation made with the help of modern NMT systems; to carry out a comparative analysis of the translation of legal texts using the methods of contextual analysis, structural-semantic and comparative-comparative analysis; to determine the limitations of the existing NMT models; to identify the advantages and limitations of the existing NMT models for the translation of legal texts. …”
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Multi-Head Graph Attention Adversarial Autoencoder Network for Unsupervised Change Detection Using Heterogeneous Remote Sensing Images by Meng Jia, Xiangyu Lou, Zhiqiang Zhao, Xiaofeng Lu, Zhenghao Shi

“…This bilateral structure mitigates the information loss associated with one-way mappings, enabling more accurate style transformation and reducing false change detections caused by sensor heterogeneity, which represents a key advantage over existing unidirectional methods. …”
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LEM-Detector: An Efficient Detector for Photovoltaic Panel Defect Detection by Xinwen Zhou, Xiang Li, Wenfu Huang, Ran Wei

“…To address these challenges, this paper proposes the LEM-Detector, an efficient end-to-end photovoltaic panel defect detector based on the transformer architecture. To address the low detection accuracy for Crack and Star crack defects and the imbalanced dataset, a novel data augmentation method, the Linear Feature Augmentation (LFA) module, specifically designed for linear features, is introduced. …”
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Beyond Granularity: Enhancing Continuous Sign Language Recognition with Granularity-Aware Feature Fusion and Attention Optimization by Yao Du, Taiying Peng, Xiaohui Hu

“…We introduce a feature fusion method for integrating visual features of disparate granularities and refine the metric of attention to enhance the Transformer’s comprehension of video content. …”
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Text-Enhanced Graph Attention Hashing for Cross-Modal Retrieval by Qiang Zou, Shuli Cheng, Anyu Du, Jiayi Chen

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Enhanced brain tumor diagnosis using combined deep learning models and weight selection technique by Karim Gasmi, Najib Ben Aoun, Najib Ben Aoun, Khalaf Alsalem, Ibtihel Ben Ltaifa, Ibrahim Alrashdi, Lassaad Ben Ammar, Manel Mrabet, Abdulaziz Shehab

“…Brain tumor classification is a critical task in medical imaging, as accurate diagnosis directly influences treatment planning and patient outcomes. Traditional methods often fall short in achieving the required precision due to the complex and heterogeneous nature of brain tumors. …”
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Image Classification Model Based on Contrastive Learning With Dynamic Adaptive Loss by Quandeng Gou, Jingxuan Zhou, Zi Li, Fangrui Zhang, Yuheng Ren

“…These experimental results fully demonstrate the effectiveness and feasibility of the proposed method.…”
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Workflow Detection with Improved Phase Discriminability by ZHANG, M., HU, H., LI, Z.

“…Specifically, temporal self-attention is firstly designed to learn the relationship between different positions of feature sequence. Then, multi-scale Transformer is introduced to encode pyramid features, which fuses multiple context cues for discriminative feature representation. …”
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