Dual-Alignment CLIP: Task-Specific Alignment of Text and Visual Features for Few-Shot Remote Sensing Scene Classification by Dongmei Deng, Ping Yao

“…To address these issues, we design a multilevel image–text feature alignment (MITA) component to align the multimodal embeddings with visual-guided text features from instance, class, and random level, and an image–image feature alignment (IIA) component to reliably measure the similarity between images by remapping these visual features from image–text alignment embedding space to image–image alignment feature space. …”
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A hybrid super learner ensemble for phishing detection on mobile devices by Routhu Srinivasa Rao, Cheemaladinne Kondaiah, Alwyn Roshan Pais, Bumshik Lee

“…Abstract In today’s digital age, the rapid increase in online users and massive network traffic has made ensuring security more challenging. …”
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DSC-Net: Enhancing Blind Road Semantic Segmentation with Visual Sensor Using a Dual-Branch Swin-CNN Architecture by Ying Yuan, Yu Du, Yan Ma, Hejun Lv

“…The hybrid attention module (HAM), embedded within the Inverted Residual Module (IRM), sharpens the detection of blind road boundaries, while the IRM improves the speed of network processing. …”
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Comparative Evaluation of Sequential Neural Network (GRU, LSTM, Transformer) Within Siamese Networks for Enhanced Job–Candidate Matching in Applied Recruitment Systems by Mateusz Łępicki, Tomasz Latkowski, Izabella Antoniuk, Michał Bukowski, Bartosz Świderski, Grzegorz Baranik, Bogusz Nowak, Robert Zakowicz, Łukasz Dobrakowski, Bogdan Act, Jarosław Kurek

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EFFResNet-ViT: A Fusion-Based Convolutional and Vision Transformer Model for Explainable Medical Image Classification by Tahir Hussain, Hayaru Shouno, Abid Hussain, Dostdar Hussain, Muhammad Ismail, Tatheer Hussain Mir, Fang Rong Hsu, Taukir Alam, Shabnur Anonna Akhy

“…To improve interpretability, EFFResNet-ViT incorporates Grad-CAM visualization techniques to highlight regions contributing to classification decisions and employs t-distributed stochastic neighbor embedding for feature space analysis, providing insights into class separability. …”
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ICT-Net: A Framework for Multi-Domain Cross-View Geo-Localization with Multi-Source Remote Sensing Fusion by Min Wu, Sirui Xu, Ziwei Wang, Jin Dong, Gong Cheng, Xinlong Yu, Yang Liu

“…To address these fundamental challenges of weak feature correlation and poor scene adaptation, we present a novel framework termed ICT-Net (Integrated CNN-Transformer Network) that synergistically combines convolutional neural networks with Transformer architectures. …”
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Functional brain networks develop from a "local to distributed" organization. by Damien A Fair, Alexander L Cohen, Jonathan D Power, Nico U F Dosenbach, Jessica A Church, Francis M Miezin, Bradley L Schlaggar, Steven E Petersen

“…Studies of development often attempt to identify the organizing principles that guide the maturation of these functional networks. In this report, we combine resting state functional connectivity MRI (rs-fcMRI), graph analysis, community detection, and spring-embedding visualization techniques to analyze four separate networks defined in earlier studies. …”
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XTNSR: Xception-based transformer network for single image super resolution by Jagrati Talreja, Supavadee Aramvith, Takao Onoye

“…In this paper, we present the XTNSR model, a novel multi-path network architecture that combines Local feature window transformers (LWFT) with Xception blocks for single-image super-resolution. …”
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Short Text Semantic Similarity Measurement Approach Based on Semantic Network by Naamah Hussien Hameed, Adel M. Alimi, Ahmed T. Sadiq

“…The network representation is a visual representation of knowledge objects, their qualities, and their relationships. …”
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Mobile detection of cataracts with an optimised lightweight deep Edge Intelligent technique by Dipta Neogi, Mahirul Alam Chowdhury, Mst. Moriom Akter, Md. Ishan Arefin Hossain

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Global Feature Focusing and Information Enhancement Network for Occluded Pedestrian Detection by ZHENG Kaikui, JI Kangyou, LI Jun, LI Qiming

“…To enhance the feature representation and reduce background noise interference, the Convolutional Block Attention Module (CBAM) is embedded after the feature maps. CBAM adjusts the importance of each channel and spatial location in the feature maps through operations like global average pooling, maxpooling, and small fully connected neural networks in both channel and spatial attention dimensions. …”
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Lightweight network for insulator fault detection based on improved YOLOv5 by Dehua Weng, Zhiliang Zhu, Zhengbing Yan, Moran Wu, Ziang Jiang, Nan Ye

“…Current fault diagnosis methods heavily depend on manual visual inspection, leading to inefficiency and inaccuracies. …”
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Weed detection in cornfields based on improved lightweight neural network model by Haicheng Wan, Shanping Wang

“…While ensuring the precise detection of small target objects such as corn seedlings and 13 types of weeds in the image, the model structure becomes more lightweight, better meeting the configuration requirements of embedded devices. Therefore, this research not only provides a theoretical basis and technical guidance for corn yield prediction and the development of a visual system for disease identification but also sets a good example for identifying other species.…”
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Edge-Aware Dual-Task Image Watermarking Against Social Network Noise by Hao Jiang, Jiahao Wang, Yuhan Yao, Xingchen Li, Feifei Kou, Xinkun Tang, Limei Qi

“…To realize this, the EASHM leverages knowledge distillation from an edge detection teacher and employs a dual-task encoder that simultaneously performs edge detection and watermark embedding through maximal parameter sharing. The framework is further equipped with a social network noise simulator (SNNS) and a secret recovery module (SRM) to enhance robustness against common image noise attacks. …”
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Transductive zero-shot learning via knowledge graph and graph convolutional networks by Qiong Li, Xin Sun, Junyu Dong

“…With a shallow graph convolutional network having a small number of layers, we learn the classifier for each category, supervised by the visual classifiers of the seen categories. …”
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A Reflection on the Visual Representation of Nationalism Discourse in Iran During the Qajar Period (A Case Study of Qajar Newspaper Images as Cultural Texts of the Modernization Pe... by Shadi Taki, Sedaghat Jabbari Kalkhoran, Yaghoub Azhand

“…In this context, discourse semiotics, focusing on the concepts within the network of codes of nationalism discourse, can interpret the motifs, visual symbols, and their applications in the aforementioned visual media, ultimately reaching their semantic roots. …”
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Untangling the Furball: A Practice Mapping Approach to the Analysis of Multimodal Interactions in Social Networks by Axel Bruns, Kateryna Kasianenko, Vish Padinjaredath Suresh, Ehsan Dehghan, Laura Vodden

“…This article introduces the analytical approach of practice mapping , using vector embeddings of network actions and interactions to map commonalities and disjunctures in the practices of social media users, as a framework for methodological advancement beyond the limitations of conventional network analysis and visualization. …”
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AGASI: A Generative Adversarial Network-Based Approach to Strengthening Adversarial Image Steganography by Haiju Fan, Changyuan Jin, Ming Li

“…Experimental results demonstrate that the AGASI method not only ensures high-quality secret images but also effectively reduces the accuracy of neural network classifiers, inducing misclassifications and significantly increasing the embedding capacity of the steganography system. …”
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High-Reputation Food Formulas: A Heterogeneous Information Network Representation and Semantic Analysis Approach by Hongfei Cui, Rui Yan, Qi Cao, Jingyu Zhang

“…We apply our approach to 1062 breakfast products and 58,206 reviews from Amazon, extracting taste- and ingredient-related sentiment while excluding non-formulation factors (e.g., price, packaging, logistics). Through embedding-based visualization, our product space groups items according to similar formulation characteristics, while the ingredient space reveals functional clusters among ingredients. …”
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Design of a Convolutional Neural Network with Type-2 Fuzzy-Based Pooling for Vehicle Recognition by Cheng-Jian Lin, Bing-Hong Chen, Chun-Hui Lin, Jyun-Yu Jhang

“…In addition, t-distributed stochastic neighbor embedding plots and feature visualization maps further highlighted the potential of type-2 fuzzy-based pooling to overcome the limitations of conventional pooling methods and enhance the performance of convolutional neural networks in image analysis tasks.…”
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