A5100460976- Multi-Agent Systems and Negotiation
- Reinforcement Learning in Robotics
- Topic Modeling
- Auction Theory and Applications
- Artificial Intelligence in Law
- Computational Drug Discovery Methods
- Spam and Phishing Detection
- Advanced Image Processing Techniques
- Complex Network Analysis Techniques
- Advanced Memory and Neural Computing
- Machine Learning in Materials Science
- Neural Networks and Applications
- Speech and dialogue systems
- Plant responses to elevated CO2
- Data-Driven Disease Surveillance
- Smart Cities and Technologies
- Genomics and Phylogenetic Studies
- stochastic dynamics and bifurcation
- Generative Adversarial Networks and Image Synthesis
- Neural dynamics and brain function
- Image and Signal Denoising Methods
- Blockchain Technology Applications and Security
- Anomaly Detection Techniques and Applications
- Advanced Technologies in Various Fields
- Cybercrime and Law Enforcement Studies
Tianjin University
2018-2024
Chongqing Jiaotong University
2023-2024
Harbin Institute of Technology
2024
Nanjing University of Aeronautics and Astronautics
2024
Fujian Normal University
2024
Anhui University
2023-2024
Shanghai Jiao Tong University
2023
Jiangxi Normal University
2023
Nantong University
2023
Shenzhen University
2023
This paper reviews the video colorization challenge on New Trends in Image Restoration and Enhancement (NTIRE) workshop, held conjunction with CVPR 2023. The target of this is converting grayscale videos into color better performance temporal consistency. consists two tracks. For Track 1, goal achieving best FID (Fréchet Inception Distance) while being constrained to maintain or improve over baseline method terms temporal-consistency metric. Color Distribution Consistency (CDC) index used as...
Abstract Background Influenza is an infectious respiratory disease that can cause serious public health hazard. Due to its huge threat the society, precise real-time forecasting of influenza outbreaks great value our public. Results In this paper, we propose a new deep neural network structure forecasts influenza-like illness rate (ILI%) in Guangzhou, China. Long short-term memory (LSTM) networks applied precisely forecast accurateness due long-term attribute and diversity epidemic data. We...
Encrypted web traffic can reveal sensitive information of a user, such as their browsing histories. Existing studies on encrypted analysis attacks usually focus fingerprinting different websites rather than that webpages from same website. Fine-grained webpage allows exploiting more private users, e.g., interests within news website or an online shopping Since have very similar features (e.g., statistical information) make them indistinguishable, existing solutions may end up with low...
Drug-induced toxicity damages the health and is one of key factors causing drug withdrawal from market. It great significance to identify drug-induced target-organ toxicity, especially detailed pathological findings, which are crucial for assessment, in early stage development process. A large variety studies have devoted toxicity. However, most them limited single organ or only binary Here we proposed a novel multi-label learning model named Att-RethinkNet, predicting findings targeted on...
Abstract N 6-methyladenosine (m6A), which is the mostly prevalent modification in eukaryotic mRNAs, involved gene expression regulation and many RNA metabolism processes. Accurate prediction of m6A important for understanding its molecular mechanisms different biological contexts. However, most existing models have limited range application are species-centric. Here we present PEA-m6A, a unified, modularized parameterized framework that can streamline m6A-Seq data analysis predicting...
<abstract><p>For tasks intractable for a single agent, agents must cooperate to accomplish complex goals. A good example is coalitional games, where group of individuals forms coalitions produce jointly and share surpluses. In such negotiation how strategically negotiate reach agreements on gain allocation however key challenge, when the are independent selfish. This work therefore employs deep reinforcement learning (DRL) build autonomous agent called DALSL that can deal with...
Influenza is a contagious respiratory disease that can lead to serious illness. Due its threat public health, accurate real-time prediction of influenza outbreaks has great value. In this paper, novel deep neural network architecture employed provide ILI% in Guangzhou, China. Because the long-term structure property and diversity epidemic data, long short-term memory (LSTM) yield accuracy. We design Multi-channel LSTM extract fused descriptor from multiple types input. further improve...
Non-fungible tokens (NFTs) are decentralized digital to represent the unique ownership of items. Recently, NFTs have been gaining popularity and at same time bringing up issues, such as scams, racism, sexism. Decentralization, a key attribute NFT, contributes some issues that easier regulate under centralized schemes, which intentionally left out NFT marketplace. In this work, we delved into centralization-decentralization dilemma in space through mixed quantitative qualitative methods....
Image deblurring problem is a tough work for improving the quality of images, in this paper; we develop an efficient and fast thresholding algorithm to handle such problem. We observe that improved iterative (IFISTA) can be further accelerated by using sequence over relaxation parameters which do not satisfy Nesterov's rule. Our proposed preserves simplicity IFISTA shrinkage (FISTA). In addition, theoretically study convergence our obtain some rate. Furthermore, investigate local variation...
In recent years, cyber-racketeering has become a prevalent means of cyberattack, severely jeopardizing nations, organizations, and individual users. However, because previous research been focused on crimes, insider security threats, compliance, the serious consequences organized cybercrimes have received little attention. To investigate cyber-racketeering, we explore how cybercriminals apply organizational techniques to systematically commit cyberattack individuals businesses. Based 80...
In order to simulate the transmission and processing of information with neurons, a memristor is used as synapse, which has an electromagnetic induction effect. This paper proposed fractional-order tabu learning neuron model memristor. Firstly, analysis model's equilibrium points reveals presence hidden attractors. Secondly, system analyzed by bifurcation diagrams, Lyapunov exponent diagrams phase found have rich dynamic behaviors. The attraction basins demonstrate that characterized...
Agent-based negotiation aims at automating process on behalf of humans to save time and efforts. While successful, the research automated focuses communication merely through offer exchange (e.g., following alternating protocol). As many real-world settings involve linguistic channel express intentions, ask questions, discuss plans so on, information bandwidth is therefore restricted grounded in action space negotiation. To bridge gap, this work proposes MCAN (Multiple Channel Automated...
In negotiation dialogue tasks, opponents may use various strategies. Such negotiations are challenging because our chatbot needs to be able detect the behavior change and then adapt its own policy accordingly. Moreover, instead of adopting stationary strategies, a more advanced opponent demonstrate sophisticated behaviors by employing reasoning strategies predict behavior. To address these challenges, this work proposes novel for dialogues, which leverages predictive power Bayesian reuse...