Adaptive Transformer-Based Deep Learning Framework for Continuous Sign Language Recognition and Translation by Yahia Said, Sahbi Boubaker, Saleh M. Altowaijri, Ahmed A. Alsheikhy, Mohamed Atri

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A Semantic Weight Adaptive Model Based on Visual Question Answering by Li Huimin, Li Xuan, Chen Yan

“…This limitation significantly hinders the models’ capacity to decipher complex relationships between objects in images and perform high-level semantic reasoning.To address this challenge and recognizing the differing natures of open-ended and closed-ended tasks, we innovatively propose a conditional reasoning model called the Semantic Weight Adaptive Model Network (SWAMN). The crux of this model lies in its ability to automatically extract task-relevant information from questions to dynamically guide the fusion process of multimodal features. …”
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Multi-Temporal Dual Polarimetric SAR Crop Classification Based on Spatial Information Comprehensive Utilization by Qiang Yin, Yuming Du, Fangfang Li, Yongsheng Zhou, Fan Zhang

“…Then, a HyperGraph adjacency matrix was constructed, and a HyperGraph neural network (HGNN) was utilized to better learn the features of plots of the same crop that are distributed far from each other. …”
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Beyond the dichotomy: understanding the overlap between atopic dermatitis and psoriasis by Mengmeng Li, Jiangyi Wang, Qingfeng Liu, Youqing Liu, Wenyao Mi, Wei Li, Wei Li, Jingyi Li

“…The review expands upon the disease spectrum hypothesis and discusses the nomenclature for conditions exhibiting features of both diseases. We critically evaluate the clinical and histopathological characteristics of concomitant psoriasis and atopic dermatitis, highlighting recent advances in molecular diagnostics for accurate disease differentiation. …”
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YOLO-TARC: YOLOv10 with Token Attention and Residual Convolution for Small Void Detection in Root Canal X-Ray Images by Yin Pan, Zhenpeng Zhang, Xueyang Zhang, Zhi Zeng, Yibin Tian

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Deep learning for rice leaf disease detection: A systematic literature review on emerging trends, methodologies and techniques by Chinna Gopi Simhadri, Hari Kishan Kondaveeti, Valli Kumari Vatsavayi, Alakananda Mitra, Preethi Ananthachari

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Comparative analysis of statistical and deep learning-based multi-omics integration for breast cancer subtype classification by Mahmoud M. Omran, Mohamed Emam, Mariam Gamaleldin, Asmaa M. Abushady, Mustafa A. Elattar, Mohamed El-Hadidi

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IchthyNet: An Ensemble Method for the Classification of In Situ Marine Zooplankton Shadowgraph Images by Brittney Slocum, Bradley Penta

“…The resulting images were then cleaned, segmented into regions of interest (ROIs), and fed through three convolutional neural networks (CNNs): VGG-16, ResNet-50, and a custom model created to find more high-level features in this dataset. …”
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Charge Diagnostics and State Estimation of Battery Energy Storage Systems Through Transformer Models by Rolando Antonio Gilbert Zequera, Anton Rassolkin, Toomas Vaimann, Ants Kallaste

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Performance Comparison of Different Pre-Trained Deep Learning Models in Classifying Brain MRI Images by Onur Sevli

“…However, the extraction of image features requires special engineering in the machine learning process. …”
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A Method Inspired by One-Dimensional Discrete-Time Quantum Walks for Influential Node Identification by Wen Liang, Yifan Wang, Qiwei Liu, Wenbo Zhang

“…This design enables the development of a simplified shift operator that leverages both self-loops and the network’s structural connectivity. Furthermore, degree centrality and path-based features are integrated into the coin operator, enhancing the accuracy and scalability of the IOQW framework. …”
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Crack Identification and Flaw Detection Eva-luation of Bolster Hanger Based on Machine Vision by YANG Fan, ZHAO Mengjiao, CHEN Ying, JIANG Xue

“…In addition, to overcome the potential information loss during the feature fusion stage of the Neck network, an enhanced BiFPN (bidirectional feature pyramid network) structure is introduced for efficient fusion of multi-scale feature maps. …”
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Application of a Transfer Learning Model Combining CNN and Self-Attention Mechanism in Wireless Signal Recognition by Wu Wei, Chenqi Zhu, Lifan Hu, Pengfei Liu

“…In this paper, we propose TransConvNet, a hybrid model combining Convolutional Neural Networks (CNNs), self-attention mechanisms, and transfer learning for wireless signal recognition under challenging conditions. …”
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Deep learning-based object detection and robotic arm grasping by ZHANG Lei, ZHANG Senhui, YAN Song, YUAN Yuan

“…Secondly, to enhance the feature extraction capabilities of the grasping network, the parallel use of different-size convolutional kernels in the Inception-ResNet module was utilized to broaden the network's receptive field. …”
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Apprentice bot model design and implementation for psychological clients’ therapy by Kibrom Gidey, Hailay Beyene, Fiseha Haileslassie, Haben Berihu

“…The syntactic and semantic structure of data and user chat's memory network were investigated. Four neural networks (LSTM, single GRU, transposed GRU and double GRU) were experimented with to find the best-fitting deep learning model. …”
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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

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EcoTaskSched: a hybrid machine learning approach for energy-efficient task scheduling in IoT-based fog-cloud environments by Asfandyar Khan, Faizan Ullah, Dilawar Shah, Muhammad Haris Khan, Shujaat Ali, Muhammad Tahir

“…To tackle these challenges, we propose a novel ML-based EcoTaskSched model, which leverages deep learning for energy-efficient task scheduling in fog-cloud networks. The proposed hybrid model integrates Convolutional Neural Networks (CNNs) with Bidirectional Log-Short Term Memory (BiLSTM) to enhance energy-efficient schedulability and reduce energy usage while ensuring QoS provisioning. …”
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M<inline-formula><tex-math notation="LaTeX">$^{2}$</tex-math></inline-formula>Convformer: Multiscale Masked Hybrid Convolution-Transformer Network for Hyperspectral Image Super-Res... by Shuo Wang, Boneng Shi, Ninglian Wang, Yuzhu Zhang, Yan Zhu

“…Extensive evaluations on three benchmark datasets demonstrate that the proposed method achieves superior performance than state-of-the-art methods.…”
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An Enhanced Framework for Assessing Pluvial Flooding Risk with Integrated Dynamic Population Vulnerability at Urban Scale by Xinyi Shu, Chenlei Ye, Zongxue Xu, Ruting Liao, Pengyue Song, Silong Zhang

“…By constructing a hydrological–hydrodynamic coupled model using the SWMM and LISFLOOD-FP, this study evaluates the drainage capacity of the pipe network and surface inundation characteristics under both historical and design rainfall scenarios. …”
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Advanced Machine Learning Techniques for Predicting Concrete Compressive Strength by Mohammad Saleh Nikoopayan Tak, Yanxiao Feng, Mohamed Mahgoub

“…After comprehensive data preprocessing and feature engineering, various regression and classification models were trained and evaluated, including gradient boosting, random forest, AdaBoost, k-nearest neighbors, linear regression, and neural networks. …”
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