The 7th Int’l Conference on Machine Learning, Pattern Recognition and Intelligent Systems (MLPRIS 2025)

The-7th-Int'l-Conference-on-Machine-Learning,-Pattern-Recognition-and-Intelligent-Systems-(MLPRIS-2025)

The 7th Int’l Conference on Machine Learning, Pattern Recognition and Intelligent Systems (MLPRIS 2025) will be held during July 18-20, 2025 in Kunming, China. The conference will cover issues on Advanced Control and Detection Technology, Artificial Neural Networks, Audio/Speech Recognition, Music Analysis, Multimedia Systems, Biometrics, Biomedical Pattern Analysis and Information Systems, Data/web Mining and Knowledge Discovery, Human-computer Interaction, etc. It dedicates to creating a stage for exchanging the latest research results and sharing the advanced research methods in related fields. MLPRIS 2024 is designed to be an interactive platform, fostering the exchange of the latest research findings and innovative research methodologies within the relevant fields. Attendees will have the opportunity to showcase their research progress, discover emerging trends, and network with fellow professionals in a collaborative environment.

Scientific Sessions

Applications Other Related Topics
Deep Learning
Reinforcement Learning
Natural Language Processing
Data/web Mining and Knowledge Discovery
Computer Vision
Bayesian Learning
Semi-Supervised Learning
Unsupervised Learning
Active Learning
Transfer Learning
Explainable AI
Image Analysis
Speech Recognition
Biometric Identification
Pattern Classification
Object Recognition
Signal Processing
Robotics and Automation
Time Series Analysis
Expert Systems
Intelligent Agents
Fuzzy Systems
Evolutionary Computation
Machine Learning
Neural Networks
Human-Computer Interaction
Multi-Agent Systems
Other Related Topics

Important Dates
Abstract Submission Opens29/11/2024
Abstract Submission Deadline09/07/2025
Abstract Submission Closes09/07/2025
Registration Opens29/11/2024
Registration Deadline09/07/2025
Registration Closes09/07/2025
Date formats: d/m/y
Event Details
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Event Details