About ICDLA 2026

The 2026 Digital Intelligence Frontier Academic Week–Guilin will take place from August 3 to 8, 2026, in Guilin, China. This premier event brings together multiple international cutting-edge conferences, focusing on deep learning, automation technologies, artificial intelligence, large language models, and intelligent systems. It aims to establish a distinguished, interdisciplinary exchange platform for scholars worldwide to jointly explore the scientific frontiers and industrial future of the digital intelligence era.

As one of the major conferences of the Academic Week, the 2026 International Conference on Deep Learning and Automation (ICDLA 2026) will take place on August 4, 2026. At a time when the core driving force of AI is deeply integrated with industrial transformation, deep learning is leading automation technology into a new phase where perception, decision-making, and control are integrated. From highly adaptive intelligent manufacturing systems, to clusters of intelligent robots capable of understanding complex environments, to large-scale collaborative optimization in smart cities and smart grids, the integration of deep learning and automation is reshaping traditional industrial landscapes and expanding new frontiers in scientific research and engineering applications.

ICDLA 2026 aims to gather global intelligence for in-depth discussions around core topics including deep learning models and algorithms, and intelligent automation systems. The conference will provide an international, high-end platform for scholars, engineers, and industry leaders worldwide: Here, you can share your latest research findings and demonstrate academic influence; engage in face-to-face exchanges with top experts in the field to spark innovative ideas; expand international collaboration networks and promote substantive scientific partnerships; and accurately grasp disciplinary development trends to gain insights into future research directions.

The topics of interest for submission include, but are not limited to:

◕ Track1: Deep Learning Models and Algorithms

Recurrent Neural Networks
Sparse Coding
Neuro-Fuzzy Algorithms
Evolutionary Computation Methods
Convolutional Neural Networks
Deep Hierarchical Networks
Unsupervised Feature Learning
Deep Boltzmann Machines
Generative Adversarial Networks, Autoencoder
Deep Belief Networks
Meta-Learning and Deep Networks
Deep Reinforcement Learning
Deep Generative Model Learning
Deep Kernel Learning
Gaussian Processes in Machine Learning
Large-Scale Model Deployment
Lightweight Models
Generative Automation
Federated Intelligence

◕Track2:  Intelligent Automation Systems

Scientific Research Agents
Industrial Intelligent Manufacturing
Intelligent Robotics
Automated Inspection
Cyber-Physical Systems
Unmanned Systems
Process Automation
Intelligent Sensing and Fusion
Automated Scheduling
Edge Intelligence
Human-Machine Collaborative Systems
Medical Automation
Energy Automation
Multimodal Automated Perception
Intelligent Decision-Making
Cross-Domain Automation
Real-Time Intelligent Scheduling
Trustworthy Automation Verification
Edge Collaborative Automation
Dynamic Scenario Automation
Human-Machine Collaborative Decision-Making

Publication

All accepted full papers will be published in the conference proceedings and will be submitted to EI Compendex / Scopus  for indexing.