A5103325669- Domain Adaptation and Few-Shot Learning
- Imbalanced Data Classification Techniques
- Data Stream Mining Techniques
- Cryptographic Implementations and Security
- Coding theory and cryptography
- Multimodal Machine Learning Applications
- Topic Modeling
- Brain Tumor Detection and Classification
- Cryptography and Data Security
- Advanced Image and Video Retrieval Techniques
- Explainable Artificial Intelligence (XAI)
- Optical Wireless Communication Technologies
- Adaptive Control of Nonlinear Systems
- Privacy-Preserving Technologies in Data
- Reinforcement Learning in Robotics
- Speech Recognition and Synthesis
- Network Security and Intrusion Detection
- COVID-19 diagnosis using AI
- AI-based Problem Solving and Planning
- Advanced Text Analysis Techniques
- Evaluation Methods in Various Fields
- Robotic Locomotion and Control
- Optical Systems and Laser Technology
- Robotic Path Planning Algorithms
- Chaos-based Image/Signal Encryption
Shanxi Agricultural University
2025
University of Chinese Academy of Sciences
2024
Technology and Engineering Center for Space Utilization
2024
Chinese Academy of Sciences
2011-2024
Jinan University
2024
Hebei North University
2024
Intelligent Health (United Kingdom)
2024
Coventry University
2024
China-Japan Friendship Hospital
2024
Pacific Medical (China)
2024
The integration of Large Language Models (LLMs) into robotic control, including drones, has the potential to revolutionize autonomous systems. Research studies have demonstrated that LLMs can be leveraged support operations. However, when facing tasks with complex reasoning, concerns and challenges are raised about reliability solutions produced by LLMs. In this paper, we propose a prompt framework enhanced reasoning enable reliable LLM-driven control for drones. Our consists novel technical...
Abstract The virtual model control (VMC) method establishes a direct correlation between the end-effector and main body by selecting appropriate mechanical components. This approach facilitates force while circumventing necessity for complex dynamic modeling. However, simplification inherent in this modeling can result inaccuracies calculation of joint driving torques, ultimately diminishing precision. Moreover, VMC typically depends on predefined models control, which constrains its...
This paper explores a hierarchical prompting mechanism for the image classification (HIC) task. Different from prior HIC methods, our is first to explicitly inject ancestor-class information as tokenized hint that benefits descendant-class discrimination. We think it well imitates human visual recognition, i.e., humans may use ancestor class prompt draw focus on subtle differences among descendant classes. model this into Transformer with Hierarchical Prompting (TransHP). TransHP consists of...
Self-supervised learning (SSL) has recently received significant attention due to its ability train high-performance encoders purely on unlabeled data-often scraped from the internet. This data can still be sensitive and empirical evidence suggests that SSL memorize private information of their training disclose them at inference time. Since existing theoretical definitions memorization supervised rely labels, they do not transfer SSL. To address this gap, we propose SSLMem, a framework for...
Trained on massive publicly available data, large language models (LLMs) have demonstrated tremendous success across various fields. While more data contributes to better performance, a disconcerting reality is that high-quality public will be exhausted in few years. In this paper, we offer potential next step for contemporary LLMs: collaborative and privacy-preserving LLM training the underutilized distributed private via federated learning (FL), where multiple owners collaboratively train...
Due to the rapid progress made in quantum computers, modern cryptography faces great challenges. Many new digital signature schemes that have resistance computing are being presented for Post-Quantum Cryptography (PQC) standardization. The Leighton-Micali (LMS), a kind of hash-based scheme, is selected as promising candidate PQC protocols by Internet Engineering Task Force (IETF) because its small private and public key sizes. However, low-efficiency generation forms bottleneck practical...
Designed and implemented a distributed data streams processing system based on Flume, Kafka Spark, fetch analyze datastreams mining business intelligence information efficiently, real-timely reliably, With high scalability reliability of the multiple sources can be collected accurately extended easily.Kafka's characteristics throughput, scalability, distribution meet requirements massive data.Spark Streaming provides set efficient, fault-tolerant real-time large-scale stream frame.Thereby...
Semantic orientations of words is an important part in the sentiment analysis. Several methods for polarity detection were briefly introduced this paper. We focused on WordNet-based and analyzed a classic one. In order to overcome shortage method, we proposed complementary method with help "second level synonym". The evaluation end paper showed that our was effective.
Numerous large language model (LLM) agents have been built for different tasks like web navigation and online shopping due to LLM's wide knowledge text-understanding ability. Among these works, many of them utilize in-context examples achieve generalization without the need fine-tuning, while few considered problem how select effectively examples. Recently, methods based on trajectory-level retrieval with task meta-data using trajectories as proposed improve agent's overall performance in...
There has been a growing interest in employing single photon avalanche diode (SPAD) array detectors for laser communication systems deep space communications. The most important factor affecting the performance of SPAD is dead time. In this paper, we investigate photocount distribution small-scale with fixed short We employed Gaussian, Poisson, and shifted Poisson to fit compare goodness various sizes. With distribution, capacity PPM-SPAD system investigated. addition, proposed new...