Underwater fish image recognition based on knowledge graphs ...
This section reviews the research progress in underwater image processing, underwater object recognition , and the application of knowledge graphs in visual tasks, and analyzes the advantages and ...
As marine science advances, the demand for efficient fish species recognition has become increasingly urgent. The manual recognition method is not only time-consuming but also requires extensive expertise in ichthyology. By integrating deep learning techniques into fish species recognition , efficiency is usually increased, which propels marine research forward. Existing methods mainly rely on ...
A video object segmentation
To this end, this paper proposes a method for fish individual recognition in underwater complex environments based on video object segmentation, which consists of three parts, including a fish individual segmentation detection module, a fish individual recognition module, and an all-in-one visualization module.
The conservation and protection of fish species are crucial tasks for aquaculture and marine biology. Recognizing fish in underwater environments is highly challenging due to poor lighting and the visual similarity between fish and the background. Conventional recognition methods are extremely time-consuming and often yield unsatisfactory accuracy. This paper proposes a new method called ...
PDF Underwater fish image recognition based on knowledge graphs ...
To systematically validate the effectiveness of the proposed Semantic Enhancement and Recognition Framework for Low-Quality Underwater Fish Images based on a Multimodal Knowledge Graph ...
Overview of Saltwater Fish Visual Recognition Needs
Moving forward, it's essential to keep these visual contexts in mind when discussing Saltwater Fish Visual Recognition Needs.
In this study, we compile MEDFISH101, a carefully curated dataset of approximately 70,000 validated images covering 101 Mediterranean fish species. Using this resource, we developed and evaluated a series of deep learning pipelines based on transfer learning of pretrained vision foundation models to achieve accurate species recognition .
The key advances of DL algorithms applied to the visual recognition and detection of aquatic animals are generalised, including datasets, algorithms and performance. The applications of DL are summarised in aquatic animals, including image detection, video detection, species classification, biomass estimation, behaviour analysis and food safety.
Towards Visual Re
Abstract Accurate fisheries data are crucial for effective and sustainable marine resource management. With the recent adoption of Electronic Monitoring (EM) systems, more video data is now being collected than can be feasibly reviewed manually. This pa-per addresses this challenge by developing an op-timized deep learning pipeline for automated fish re-identification (Re-ID) using the novel ...
Coral reefs are among the most biodiverse marine ecosystems, playing irreplaceable roles in maintaining marine ecological balance and coastal services. Under dual pressures of global climate change and human activities, coral bleaching and degradation have become increasingly frequent, creating an urgent need for large-scale, long-term, and highly automated monitoring technologies. In recent ...
