Transformer attention fusion for fine grained medical image classification by Danyal Badar, Junaid Abbas, Raed Alsini, Tahir Abbas, Wang ChengLiang, Ali Daud

“…Our solution to these problems includes MSCAS-Net (Multi-Scale Cross and Self-Attention Network), which uses the Swin Transformer as the backbone. It extracts features at three different resolutions (12 × 12, 24 × 24, 48 × 48), allowing it to detect subtle local features and global elements. …”
Get full text

From Warlords to Politicians: Transforming Rebel Movements Into Political Parties by DENISOVA Tatyana Sergeevna, KOSTELYANETS Sergey Valerianovich

“…To achieve this, they employ many different strategies: transforming their armed groups into political parties, joining existing political organizations, establishing totally new parties, or conducting individual political activity. …”
Get full text

CNN–Transformer Hybrid Architecture for Underwater Sonar Image Segmentation by Juan Lei, Huigang Wang, Zelin Lei, Jiayuan Li, Shaowei Rong

“…Inspired by multimodal feature fusion learning, we propose a hybrid CNN–Transformer–Mamba architecture, termed FLSSNet. FLSSNet is built upon a CNN and Transformer backbone network, integrating four core submodules to address various technical challenges: (1) The asymmetric dual encoder–decoder (ADED) is capable of simultaneously extracting features from different modalities and systematically modeling both local contextual information and global spatial structure. (2) The Transformer feature converter (TFC) module optimizes the multimodal feature fusion process through feature transformation and channel compression. (3) The long-range correlation attention (LRCA) module enhances CNN’s ability to model long-range dependencies through the collaborative use of convolutional kernels, selective sequential scanning, and attention mechanisms, while effectively suppressing noise interference. (4) The recursive contour refinement (RCR) model refines edge contour information through a layer-by-layer recursive mechanism, achieving greater precision in boundary details. …”
Get full text

The application of fourier integral transforms in a general theory of diffraction by Roman WYRZYKOWSKI

“…Integral transforms have frequently been used to solve different specific problems in diffraction. …”
Get full text

ON THE CHANGE OF VALUES OF POSTNOMINATIVE APPENDICES IN THE PROCESS OF TRANSFORMATION IN THE MODERN ENGLISH by Sevil M. Radjabova

“…After all, the same adjective behaves differently in relation to transformation into different attributive complexes. …”
Get full text

Damage Localization of Piles Based on Complex Continuous Wavelet Transform: Numerical Example and Experimental Verification by Wenting Zheng, Sifan Wang, Chengxu Lin, Xianying Yu, Jingliang Liu

“…A new signal processing method called complex continuous wavelet transform (CCWT) is introduced in this paper to localize pile damage because it clearly reveals inherent characteristics of response signals. …”
Get full text

Singularity transformation through single-pass phase modulation of light by Laxminarayan, Srinivasa Rao Allam, Takashige Omatsu, Praveen Kumar

Get full text

Arithmetically Fast Position Transformation for View Synthesis and Depth Estimation by Krzysztof Wegner, Tomasz Grajek, Krzysztof Klimaszewski

“…In this paper we present a method of fast computation of matrix transformation in the process of position transformation of objects of the scene between different, virtual or real, camera positions. …”
Get full text

Text Classification of News Using Transformer-based Models for Portuguese by Isabel N. Santana, Raphael S. Oliveira, Erick G. S. Nascimento

“…This work proposes the use of a fine-tuned Transformers-based Natural Language Processing (NLP) model called BERTimbau to generate the word embeddings from texts published in a Brazilian newspaper, to create a robust NLP model to classify news in Portuguese, a task that is costly for humans to perform for big amounts of data. …”
Get full text

Vision Transformer and Brain Connectivity Patterns for Estimating Cognitive States by Debashis Das Chakladar

“…The transformer model is excellent at handling time series signals (such as electroencephalography: EEG) because it can extract information from long-term dependencies effectively. …”
Get full text

Numerical Simulation of Seismoacoustic Wave Transformation at Sea–Land Interface by Grigory Dolgikh, Mikhail Bolsunovskii, Denis Zharkov, Ruslan Zhostkov, Dmitriy Presnov, Andrey Razin, Andrey Shurup

“…It is shown that in field experiment conditions the hydroacoustic signal generated by an underwater source with a power of ~200 W is transformed into a seismic wave on the shore with an amplitude of units of nanometers at distances of several kilometers, which can be measured by a sensitive sensor. …”
Get full text

The influence of transformational leadership and leader-member exchange on project success by Đoàn Thị Thanh Thúy, Trịnh Thùy Anh

“…The study focuses on projects completed within the last 05 years in major cities across different regions of Vietnam. Applying the PLS-SEM technique for multivariate data analysis, a survey of 437 project managers with a snowball sampling method reveals that transformational leadership favors project success. …”
Get full text

Identifying Bias in Deep Neural Networks Using Image Transforms by Sai Teja Erukude, Akhil Joshi, Lior Shamir

“…The method is based on applying several image transforms to the original images, including Fourier transform, wavelet transforms, median filter, and their combinations. …”
Get full text

Leveraging Perspective Transformation for Enhanced Pothole Detection in Autonomous Vehicles by Abdalmalek Abu-raddaha, Zaid A. El-Shair, Samir Rawashdeh

“…This paper introduces a novel approach that utilizes perspective transformation to enhance pothole detection at different distances, focusing particularly on distant potholes. …”
Get full text

Chinese Paper-Cutting Style Transfer via Vision Transformer by Chao Wu, Yao Ren, Yuying Zhou, Ming Lou, Qing Zhang

“…Therefore, this paper proposes a new method for Chinese paper-cutting style transformation based on the Transformer, aiming at realizing the efficient transformation of Chinese paper-cutting art styles. …”
Get full text

Effects of Temperature and Carrier Gas on Phosphorus Transformation in Biosolids Biochar by Shefali Aktar, Md Afzal Hossain, Gabriel Gasco, Ana Mendez, Cicero Celio de Figueiredo, Kalpit Shah, Jorge Paz-Ferreiro

“…The Hedley chemical sequential extraction method and ³¹P liquid NMR were used for P characterization and quantification. …”
Get full text

BinaryViT: Binary Vision Transformer for Hyperspectral Image Classification by Xiang Hu, Taolin Liu, Zhe Guo, Yuxiang Tang, Yuanxi Peng, Tong Zhou

“…Vision transformers have demonstrated remarkable performance in hyperspectral image classification tasks. …”
Get full text

A callus transformation system for gene functional studies in soybean by Kun XU, Xiao-mei ZHANG, Cheng-ming FAN, Fu-lu CHEN, Jin-long ZHU, Shi-long ZHANG, Qing-shan CHEN, Yong-fu FU

“…Obtaining transgenic plants is a common method for analyzing gene function. Unfortunately, stable genetic transformation is difficult to achieve, especially for plants (e.g., soybean), which are recalcitrant to genetic transformation. …”
Get full text

ICAFormer: An Image Dehazing Transformer Based on Interactive Channel Attention by Yanfei Chen, Tong Yue, Pei An, Hanyu Hong, Tao Liu, Yangkai Liu, Yihui Zhou

“…To address the limitations of traditional dehazing algorithms—particularly in global feature association and local detail preservation—this study proposes a novel Transformer-based dehazing model enhanced by an interactive channel attention mechanism. …”
Get full text

Adaptive multimodal transformer based on exchanging for multimodal sentiment analysis by Gulanbaier Tuerhong, Feifan Fu, Mairidan Wushouer

“…Abstract Multimodal sentiment analysis significantly improves sentiment classification performance by integrating cross-modal emotional cues. However, existing methods still face challenges in key issues such as modal distribution differences, cross-modal interaction efficiency, and contextual correlation modeling. …”
Get full text