💻 computer science

Enhanced Gold Mining Optimization with Dual-Layer Information Sharing and Dynamic Control for Multi-Objective Scheduling of Heterogeneous UAV Swarms

This paper proposes an Improved Gold Mine Optimization Algorithm with a dual-layer information-sharing framework and dynamic Pareto dominance (IGMO-DP) to effectively solve the multi-objective scheduling problem of heterogeneous UAV swarms by simultaneously optimizing mission completion time, energy consumption, and load balance, demonstrating superior convergence and solution diversity compared to state-of-the-art algorithms.

Zhongming Lin, Siyuan Wei2026-07-09
💻 computer science

Queue-Aware Task Offloading in the ComputingContinuum under Dynamic Workloads

This paper proposes a queue-aware task offloading method for the computing continuum that hybridizes an analytically corrected G/G/c delay approximation with real-time queue observations to dynamically assign tasks under variable workloads, thereby significantly reducing latency and estimation error compared to existing baselines without requiring training or calibration.

Lluis Mas, Jordi Mateo, Jordi Vilaplana, Josep Rius2026-07-09
💻 computer science

DPENet: A Dynamic Perception Enhancement Network for Object Detection in Remote Sensing Images

This paper proposes DPENet, a dynamic perception enhancement network that integrates adaptive dynamic convolution, deformable attention, and dynamic sampling modules to effectively address challenges like varying target sizes, dense small objects, and complex backgrounds in high-resolution remote sensing image detection.

Xiaoxiao wang, Xia Zou, Meng Sun, Chong Jia, Yongqiang Xie, Xiongwei Zhang2026-07-09
💻 computer science

E-Taste Signal Encoding and Classification via Multi- Attention Residual Networks Using sEMG Streams in Virtual Sensory Systems

This study introduces a novel MACB-ResNet deep learning model that significantly improves the accuracy of classifying virtual taste stimuli from facial surface electromyography (sEMG) signals to 86.32%, outperforming traditional and standard deep learning classifiers for applications in digital health and food technology.

Zhendong Song, Asif Ullah, Majad Mansoor, You Wang2026-07-09✓ Author reviewed
💻 computer science

Enhanced Seam Segmentation for Automated Welding Robot in Construction Through Transfer Learning: Addressing Limitations of Bilateral Segmentation Network

This study proposes a transfer learning-based framework that enhances BiSeNetV2 with a hybrid Cross-Entropy–Lovasz loss to achieve robust, real-time seam segmentation for autonomous robotic welding in construction, significantly improving performance on reflective surfaces without increasing computational complexity.

Keonvin Park, Yong Ann Voeurn, Hyeokjun Kweon, Doyun Lee2026-07-09
💻 computer science

TITAN: Three-Tier Intrusion-Detection Tree-Based Adaptive Network for Industrial Internet of Things 

TITAN is a novel three-tier federated learning architecture for Industrial IoT intrusion detection that overcomes non-IID data and class imbalance challenges by exchanging only prediction outputs and device summaries via adaptive knowledge distillation and Bayesian aggregation, achieving superior macro-F1 performance over existing methods without requiring raw data or gradient sharing.

Sandeep Ghosh, Mohammed Al-Khafajiy, Saeid Pourroostaei Ardakani Ardakani2026-07-09
💻 computer science

Privacy-Utility Tradeoffs in Hierarchical Federated Learning Under Combined Differential Privacy and CKKS Homomorphic Encryption for Distributed Healthcare Networks

This paper proposes a hierarchical federated learning framework for healthcare that integrates client-level differential privacy with institution-level CKKS homomorphic encryption, demonstrating that while differential privacy incurs measurable accuracy losses dependent on the privacy budget, homomorphic encryption introduces no utility degradation, thereby isolating and quantifying the distinct privacy-utility tradeoffs of each mechanism.

Sayed Mohammed Alwedaei, Jenan Moosa2026-07-09