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Conclusions of AI in Fisheries

This will conclude this week’s speech video. Prof. Wu concludes SMARTFISH H2020 goals and their results. In summary, the project uses artificial intelligence and machine learning methods to automatically process …

Impact of SMARTFISH

Prof. Wu has already introduced SMARTFISH project. The goal of the project is to develop a high-tech system that, through automated data collection, can optimize fishing efficiency and reduce the …

Results of SMARTFISH

Prof. Wu will talk about the result of SMARTFISH H2020 project. What’s the goal that they target to achieve? In this project, researchers develop the submarine fish detection system to …

How AI Combines with Sustainable Fisheries

According to the research, more than 40% of all fishery products for human consumption worldwide are from aquaculture. However, due to the impact of global climate change, global warming has …

SMARTFISH Concept and Goals

SMARTFISH is an international research project developed to be tested and promoted in the EU fisheries sector. You can check on their official website for more details. The goals of …

Automatic Catch Analysis System

Next, Prof. Wu will explain Automatic Catch Analysis System. How does AI involve in SMARTFISH H2020? In the previous step, we have talked about the data collected for resource control. …

Deep Reinforcement Learning: Part1

Prof. Lai will introduce what is deep reinforcement learning. Deep reinforcement learning is a category of machine learning and artificial intelligence where intelligent machines can learn from their actions similar …

Fishery Management Types

Prof. Wu will talk about current methods of management of fisheries. There are three fishery management types: investment management, output management, and quota management. He will explain in detail of …

Application on VIVID

Prof. Lai continues to give examples of VIVID: Virtual Environment for Visual Deep Learning. The ultimate goal of VIVID is to simulate real-life events. One of the examples is campus …

VIVID: Virtual Environment for Visual Deep Learning

Prof. Lai introduces VIVID: Virtual Environment for Visual Deep Learning in this video. VIVID can be applied in different areas: Semantic Segmentation, Depth Prediction, Autonomous Navigation, Action Recognition. Prof. Lai …

Management of Fisheries

In this video, Prof. Wu first tells the management of fisheries. Modern fisheries management is often referred to as a governmental system of appropriate management rules based on defined objectives …

Introduction of Fisheries

Continuing on the introduction, Prof. Wu will first talk about the environmental impact. The natural resources are depleted. How serious this problem could be? As the population of the earth …

Virtual-to-Real Learning

What is the real world look like for drones? We can see from the slide. Prof. Lai will talk about applications using deep reinforcement learning. Nowadays, big companies and researchers …

Deep Reinforcement Learning: Part2

Continung on explaining deep reinforcement learning, Prof. Lai first talks about the fundamental problem of Reinforcement Learning, exploration versus exploitation problem. Then, he tells the Q-learning, which is a common …