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相关论文: A deep neural network for multi-species fish detec…

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The target of this paper is to recommend a way for Automated classification of Fish species. A high accuracy fish classification is required for greater understanding of fish behavior in Ichthyology and by marine biologists. Maintaining a…

计算机视觉与模式识别 · 计算机科学 2018-05-28 Dhruv Rathi , Sushant Jain , Dr. S. Indu

Jellyfish, a diverse group of gelatinous marine organisms, play a crucial role in maintaining marine ecosystems but pose significant challenges for biodiversity and conservation due to their rapid proliferation and ecological impact.…

计算机视觉与模式识别 · 计算机科学 2025-07-16 Md. Sabbir Hossen , Md. Saiduzzaman , Pabon Shaha , Mostofa Kamal Nasir

Clean energy from oceans and rivers is becoming a reality with the development of new technologies like tidal and instream turbines that generate electricity from naturally flowing water. These new technologies are being monitored for…

计算机视觉与模式识别 · 计算机科学 2018-11-06 Wenwei Xu , Shari Matzner

Given a sufficiently large training dataset, it is relatively easy to train a modern convolution neural network (CNN) as a required image classifier. However, for the task of fish classification and/or fish detection, if a CNN was trained…

计算机视觉与模式识别 · 计算机科学 2019-11-05 Dmitry A. Konovalov , Alzayat Saleh , Michael Bradley , Mangalam Sankupellay , Simone Marini , Marcus Sheaves

Uses of underwater videos to assess diversity and abundance of fish are being rapidly adopted by marine biologists. Manual processing of videos for quantification by human analysts is time and labour intensive. Automatic processing of…

计算机视觉与模式识别 · 计算机科学 2018-07-17 Ranju Mandal , Rod M. Connolly , Thomas A. Schlacherz , Bela Stantic

A wide range of applications in marine ecology extensively uses underwater cameras. Still, to efficiently process the vast amount of data generated, we need to develop tools that can automatically detect and recognize species captured on…

计算机视觉与模式识别 · 计算机科学 2020-05-18 Kristian Muri Knausgård , Arne Wiklund , Tonje Knutsen Sørdalen , Kim Halvorsen , Alf Ring Kleiven , Lei Jiao , Morten Goodwin

Marine scientists use remote underwater video recording to survey fish species in their natural habitats. This helps them understand and predict how fish respond to climate change, habitat degradation, and fishing pressure. This information…

计算机视觉与模式识别 · 计算机科学 2022-04-19 Alzayat Saleh , Marcus Sheaves , Mostafa Rahimi Azghadi

Our understanding and ability to effectively monitor and manage coastal ecosystems are severely limited by observation methods. Automatic recognition of species in natural environment is a promising tool which would revolutionize video and…

Automatic identification of animal species by their vocalization is an important and challenging task. Although many kinds of audio monitoring system have been proposed in the literature, they suffer from several disadvantages such as…

音频与语音处理 · 电气工程与系统科学 2020-02-25 Weitao Xu , Xiang Zhang , Lina Yao , Wanli Xue , Bo Wei

In this work, we investigate a Deep Learning (DL) approach to fish segmentation in a small dataset of noisy low-resolution images generated by a forward-looking multibeam echosounder (MBES). We build on recent advances in DL and…

计算机视觉与模式识别 · 计算机科学 2020-06-17 Jesper Haahr Christensen , Lars Valdemar Mogensen , Ole Ravn

With the rapid advancement of technology, the recognition of underwater acoustic signals in complex environments has become increasingly crucial. Currently, mainstream underwater acoustic signal recognition relies primarily on…

声音 · 计算机科学 2024-01-08 Minghao Chen

Effective conservation of maritime environments and wildlife management of endangered species require the implementation of efficient, accurate and scalable solutions for environmental monitoring. Ecoacoustics offers the advantages of…

声音 · 计算机科学 2025-07-29 Burla Nur Korkmaz , Roee Diamant , Gil Danino , Alberto Testolin

Marine animals and deep underwater objects are difficult to recognize and monitor for safety of aquatic life. There is an increasing challenge when the water is saline with granular particles and impurities. In such natural adversarial…

计算机视觉与模式识别 · 计算机科学 2024-01-24 Sanyam Jain

Accurate fish segmentation in underwater videos is challenging due to low visibility, variable lighting, and dynamic backgrounds, making fully-supervised methods that require manual annotation impractical for many applications. This paper…

计算机视觉与模式识别 · 计算机科学 2025-02-27 Alzayat Saleh , Marcus Sheaves , Dean Jerry , Mostafa Rahimi Azghadi

Tracking fish movements and sizes of fish is crucial to understanding their ecology and behaviour. Knowing where fish migrate, how they interact with their environment, and how their size affects their behaviour can help ecologists develop…

计算机视觉与模式识别 · 计算机科学 2025-02-27 Alzayat Saleh , Marcus Sheaves , Dean Jerry , Mostafa Rahimi Azghadi

The fish target detection algorithm lacks a good quality data set, and the algorithm achieves real-time detection with lower power consumption on embedded devices, and it is difficult to balance the calculation speed and identification…

计算机视觉与模式识别 · 计算机科学 2021-04-13 Yang Liu , Shengmao Zhang , Fei Wang , Wei Fan , Guohua Zou , Jing Bo

This paper presents a novel deep learning approach for analyzing massive underwater acoustic data by leveraging a model trained on a broad spectrum of non-underwater (aerial) sounds. Recognizing the challenge in labeling vast amounts of…

声音 · 计算机科学 2024-02-22 Jeongsoo Park , Dong-Gyun Han , Hyoung Sul La , Sangmin Lee , Yoonchang Han , Eun-Jin Yang

Dead fish frequently appear on the water surface due to various factors. If not promptly detected and removed, these dead fish can cause significant issues such as water quality deterioration, ecosystem damage, and disease transmission.…

计算机视觉与模式识别 · 计算机科学 2024-09-04 Qingbin Tian , Yukang Huo , Mingyuan Yao , Haihua Wang

This paper presents AquaSignal, a modular and scalable pipeline for preprocessing, denoising, classification, and novelty detection of underwater acoustic signals. Designed to operate effectively in noisy and dynamic marine environments,…

声音 · 计算机科学 2025-05-21 Eirini Panteli , Paulo E. Santos , Nabil Humphrey

Quantifying fish community structure is essential for understanding biodiversity and ecosystem responses in a changing environment, yet existing survey methods provide limited high-frequency, quantitative observations. Conventional…

计算机视觉与模式识别 · 计算机科学 2026-05-12 Kota Ishikawa , Takuma Masui , Keita Koeda , Rickdane Gomez , Lucas Yutaka Kimura , Michio Kondoh
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