Deep blur detection network with boundary-aware multi-scale features by Xiaoli Sun, Qiwei Wang, Xiujun Zhang, Chen Xu, Weiqiang Zhang

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Anomalous Node Detection in Blockchain Networks Based on Graph Neural Networks by Ze Chang, Yunfei Cai, Xiao Fan Liu, Zhenping Xie, Yuan Liu, Qianyi Zhan

“…The blockchain transaction network formed during user transactions can be represented as a graph consisting of nodes and edges, making it suitable for a graph data structure. …”
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Improving Road Semantic Segmentation Using Generative Adversarial Network by Arnick Abdollahi, Biswajeet Pradhan, Gaurav Sharma, Khairul Nizam Abdul Maulud, Abdullah Alamri

“…In this study, we propose a generative adversarial network (GAN)-based deep learning approach for road segmentation from high-resolution aerial imagery. …”
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Graph Contrastive Pre-training for Anti-money Laundering by Hanbin Lu, Haosen Wang

“…Abstract Anti-money laundering (AML) is vital to maintaining financial markets, social stability, and political authority. At present, many studies model the AML task as the graph and leverage graph neural network (GNN) for node/edge classification. …”
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Development of a Modified CycleGAN Model with Residual Blocks and Perceptual Loss for Image Dehazing by Sani Moch Sopian, Arief Suryadi Satyawan, Mokhammad Mirza Etnisa Haqiqi, Helfy Susilawati, Beni Wijaya, Khaulyca Arva Artemysia, Firman, Muhammad Ikbal Samie

“…Qualitatively, this model generated clearer, more natural images with improved edge sharpness and detail preservation. These findings demonstrate that the modified CycleGAN significantly enhances dehazing performance and presents a valuable contribution to deep learning-based image restoration. …”
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The Attitudes of the Telecommunication Customers in the COVID-19 Outbreak: The Effect of the Feature Selection Approach in Churn Analysis by Handan Donat, Saliha Karadayı Usta

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Consumer Behaviour: Analysing Marketing Campaigns through Recommender Systems and Statistical Techniques

“…By decoding consumption trends, businesses can optimize their marketing strategies and improve customer satisfaction, strengthening their competitive edge in a constantly shifting market. Finally, incorporating recommender systems with artificial intelligence and machine learning tools for collaborative filtering can further refine these strategies, substantially boosting marketing efficacy.…”
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Achieving Faster and Smarter Chest X-Ray Classification With Optimized CNNs by Hassen Louati, Ali Louati, Khalid Mansour, Elham Kariri

“…In this paper, we present a three-stage framework to enhance X-ray image classification using Neural Architecture Search (NAS), Transfer Learning, and Model Compression via filter pruning, specifically targeting the ChestX-Ray14 dataset. …”
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Encoding Holographic Data Into Synthetic Video Streams for Enhanced Microplastic Detection by Paolo Russo, Fabiana Di Ciaccio, Pasquale Santaniello, Teresa Cacace, Pierluigi Carcagni, Marco del Coco, Melania Paturzo

“…This study presents a novel deep learning pipeline for the detection and classification of microplastics using digital holography, with a focus on synthetic microfibers released during laundry. …”
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A Motion‐Sensing Integrated Soft Robot with Triboelectric Nanogenerator for Pipeline Inspection by Rui Chen, Huigang Wang, Haoji Wang, Huijiang Wang, Li Bai, Xinpei Ai, Lifu Liu, Zhihao Hu, Zean Yuan

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STARMAP: Spaceborne Target Acquisition Radar With Meta-RL Assisted Placement by Alireza Famili, Shihua Sun, Tolga Atalay, Angelos Stavrou

“…Traditional methods fail to detect low-observable (LO) UASs effectively, thus presenting considerable threats in defense and civil sectors. …”
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Multiclass CNN Approach for Automatic Classification of Dolphin Vocalizations by Francesco Di Nardo, Rocco De Marco, Daniel Li Veli, Laura Screpanti, Benedetta Castagna, Alessandro Lucchetti, David Scaradozzi

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Harnessing the Green Spirit: The Impact of Spiritual Leadership on Employee Creativity in Small and Medium-Scale Enterprises by Muhammad Taimoor, Mohammad Fakhrul Islam, Muhammad Atif Bashir, Poór József, Szabó Katalin

“… Background: Creativity, innovation, and learning behaviour are essential in accomplishing a competitive edge and the prerequisite of leadership in enhancing employee creativity and organisational growth. …”
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Detecting Emerging DGA Malware in Federated Environments via Variational Autoencoder-Based Clustering and Resource-Aware Client Selection by Ma Viet Duc, Pham Minh Dang, Tran Thu Phuong, Truong Duc Truong, Vu Hai, Nguyen Huu Thanh

“…Detecting such evolving threats is especially challenging in decentralized environments where raw traffic data cannot be aggregated due to privacy or policy constraints. To address this, we present FedSAGE, a security-aware federated intrusion detection framework that combines Variational Autoencoder (VAE)-based latent representation learning with unsupervised clustering and resource-efficient client selection. …”
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Multimodal AI/ML for discovering novel biomarkers and predicting disease using multi-omics profiles of patients with cardiovascular diseases by William DeGroat, Habiba Abdelhalim, Elizabeth Peker, Neev Sheth, Rishabh Narayanan, Saman Zeeshan, Bruce T. Liang, Zeeshan Ahmed

“…The efficient synthesis and analysis of this data through integrated approach that characterizes genetic variants alongside expression patterns linked to emerging phenotypes, can reveal novel biomarkers and enable the segmentation of patient populations based on personalized risk factors. In this study, we present a cutting-edge methodology rooted in the integration of traditional bioinformatics, classical statistics, and multimodal machine learning techniques. …”
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Human Action Recognition Method Based on Multi-channel Fusion by Zhiyong TAO, Xijun GUO, Xiaokui REN, Ying LIU, Zemin WANG

“…Objective With the continuous development of science and technology, cutting-edge advancements such as artificial intelligence and deep learning increasingly penetrate various fields, significantly improving social productivity. …”
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3D IntelliGenes: AI/ML application using multi-omics data for biomarker discovery and disease prediction with multi-dimensional visualization by Rishabh Narayanan, Elizabeth Peker, William DeGroat, Dinesh Mendhe, Saman Zeeshan, Zeeshan Ahmed

“…Abstract Background The cutting-edge artificial intelligence (AI) and machine learning (ML) techniques have proven effective at uncovering elucidative knowledge on disease-causing biomarkers and the biological underpinnings of a plethora of human diseases. …”
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Automatic Identification Model for Landslide Disaster Using Remote Sensing Images Based on Improved Multiresunet by Zhenyu Zhao, Shucheng Tan, Qinghua Zhang, Hui Chen

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Traffic Management System Using YOLO Algorithm by Pankaj Kunekar, Yogita Narule, Richa Mahajan, Shantanu Mandlapure, Eshan Mehendale, Yashashri Meshram

“…Embedded controllers that adopt the transfer learning methodology can implement YOLO.…”
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ReAHGN: Adaptive Heterogeneous Graph Neural Network With Relation-Aware Embedding by Xiaoyu Zhu, Xinzhe Yu, Enze Zha, Shiyang Lin

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