3rd International Conference on Cloud Computing and Computer Networks CCCN 2025

The book consists of peer reviewed and presented papers of the 3rd International Conference on Cloud Computing and Computer Network (CCCN 2025), which took place in Singapore during May 16-18, 2025. The conference is held annually to gather scholars, researchers and engineers working in the field of cloud computing to share their newest research findings and results, discuss and exchange their thoughts and information, and learn about cutting-edge technologies. The papers are solicited on a broad range of topics, including cloud computing and semantic web technologies, cloud computing models, simulations and designs, cloud computing applications, cloud computing services, mobile cloud networking, service-oriented architecture in cloud computing, Case studies and theories in cloud computing, Cloud storage and file systems, Blockchain for emerging networks, network management, measurement and analysis, and network virtualization.

Introduction.- Application of convolutional neural networks for the detection of diseases in the CCN-51 cocoa fruit by means of a mobile application.- Target Detection Algorithm of Forward Looking Sonar Based on Swin Transformer.- An Optimization Strategy for Efficient Facial Landmark Detection Based on Improved Pixel-in-pixel Net Model.- Nonlinear Filter Combined Regularization of Compressed Sensing for CT Image Reconstruction. Vulnerabilities in Office Printers, Multifunction Printers (MFP), 3D Printers and Digital Copiers, A gateway to breach our enterprise network.- Provisioning Deep Learning Inference on a Fog Computing Architecture.- A Comparative Analysis of VPN Applications and Their Security Capabilities Towards Security Issues.- Improved Grey Wolf Optimization Algorithm Based on Logarithmic Inertia Weight.- Radio Frequency Identification Vulnerabilities: An Analysis on RFID-Related Physical Controls in an Infrastructure.- Analysis of Bee Population and the Relationship with Time.- Synthetic speech data generation using Generative Adversarial Networks.- Prediction of bee population and number of beehives  required for pollination of a 20-acre parcel crop.- Conclusion.

Lei Meng has been Professor with the School of Software, Shandong University since 2020. He received PhD in Nanyang Technological University (NTU) in 2015, and subsequently conducted postdoc research at NTU and National University of Singapore (NUS), respectively. His research interests include multimedia analysis and deep learning, with a focus on image/video representation, multimodal information fusion, and personalized user preference modeling. He has published a book with Springer and more than sixty conference and journal papers at top and renowned venues, such as TKDE, TOIS, TNNLS, TMM, MM, SIGGRAPH, SIGIR, WWW, ICML, IJCAI and AAAI. He has filed twenty international patents and taken in charge of two national program from the national natural science foundation of China. He actively worked with industries, and the research outcomes have received three Provincial Science and Technology Progress Awards. He is an associate editor of Applied Soft Computing and have served as Program/Technical Committee Members and Reviewers for top-tier conferences and journals in the fields of multimedia, computer vision, and data mining.