Imagen de Portada

How to Track and Segment Fish without Human Annotations: A Self-Supervised Deep Learning Approach

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Saleh, Alzayat, Sheaves, Marcus, Jerry, Dean, Azghadi, Mostafa Rahimi
Formato:	Preprint
Publicado:	2022
Materias:	Computer Vision and Pattern Recognition
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Overcoming Annotation Bottlenecks in Underwater Fish Segmentation: A Robust Self-Supervised Learning Approach
por: Saleh, Alzayat, et al.
Publicado: (2022)

Adaptive deep learning framework for robust unsupervised underwater image enhancement
por: Saleh, Alzayat, et al.
Publicado: (2022)

Depth-Resolved Coral Reef Thermal Fields from Satellite SST and Sparse In-Situ Loggers Using Physics-Informed Neural Networks
por: Saleh, Alzayat, et al.
Publicado: (2026)

Weed Detection in Challenging Field Conditions: A Semi-Supervised Framework for Overcoming Shadow Bias and Data Scarcity
por: Saleh, Alzayat, et al.
Publicado: (2025)

Multi-label Instance-level Generalised Visual Grounding in Agriculture
por: Haghighat, Mohammadreza, et al.
Publicado: (2026)

A Practical Approach to Underwater Depth and Surface Normals Estimation
por: Saleh, Alzayat, et al.
Publicado: (2024)

Semi-Supervised Weed Detection for Rapid Deployment and Enhanced Efficiency
por: Saleh, Alzayat, et al.
Publicado: (2024)

FieldNet: Efficient Real-Time Shadow Removal for Enhanced Vision in Field Robotics
por: Saleh, Alzayat, et al.
Publicado: (2024)

Analyzing mixed construction and demolition waste in material recovery facilities: evolution, challenges, and applications of computer vision and deep learning
por: Langley, Adrian, et al.
Publicado: (2024)

Sugarcane Health Monitoring With Satellite Spectroscopy and Machine Learning: A Review
por: Waters, Ethan Kane, et al.
Publicado: (2024)

Advancements in Weed Mapping: A Systematic Review
por: Jahanbakht, Mohammad, et al.
Publicado: (2025)

AFFormer: Adaptive Feature Fusion Transformer for V2X Cooperative Perception under Channel Impairments
por: Zhou, Xi, et al.
Publicado: (2026)

Machine Learning for Asymptomatic Ratoon Stunting Disease Detection With Freely Available Satellite Based Multispectral Imaging
por: Waters, Ethan Kane, et al.
Publicado: (2024)

Semi-Self-Supervised Domain Adaptation: Developing Deep Learning Models with Limited Annotated Data for Wheat Head Segmentation
por: Ghanbari, Alireza, et al.
Publicado: (2024)

How to Efficiently Annotate Images for Best-Performing Deep Learning Based Segmentation Models: An Empirical Study with Weak and Noisy Annotations and Segment Anything Model
por: Zhang, Yixin, et al.
Publicado: (2023)

Semi- and Weakly-Supervised Learning for Mammogram Mass Segmentation with Limited Annotations
por: Xiong, Xinyu, et al.
Publicado: (2024)

Self-Supervised Human Activity Recognition with Localized Time-Frequency Contrastive Representation Learning
por: Taghanaki, Setareh Rahimi, et al.
Publicado: (2022)

Shifting to Machine Supervision: Annotation-Efficient Semi and Self-Supervised Learning for Automatic Medical Image Segmentation and Classification
por: Singh, Pranav, et al.
Publicado: (2023)

VideoSAVi: Self-Aligned Video Language Models without Human Supervision
por: Kulkarni, Yogesh, et al.
Publicado: (2024)

Learning to Count without Annotations
por: Knobel, Lukas, et al.
Publicado: (2023)

Good Deep Features to Track: Self-Supervised Feature Extraction and Tracking in Visual Odometry
por: Gottam, Sai Puneeth Reddy, et al.
Publicado: (2025)

Vehicle-to-Everything Cooperative Perception for Autonomous Driving
por: Huang, Tao, et al.
Publicado: (2023)

Segment Anything without Supervision
por: Wang, XuDong, et al.
Publicado: (2024)

Decoupled Spatio-Temporal Consistency Learning for Self-Supervised Tracking
por: Zheng, Yaozong, et al.
Publicado: (2025)

Boosting Self-Supervised Tracking with Contextual Prompts and Noise Learning
por: Zheng, Yaozong, et al.
Publicado: (2026)

Learning Accurate Segmentation Purely from Self-Supervision
por: You, Zuyao, et al.
Publicado: (2026)

Self-Supervised Alignment Learning for Medical Image Segmentation
por: Li, Haofeng, et al.
Publicado: (2024)

Self-Supervised ImageNet Representations for In Vivo Confocal Microscopy: Tortuosity Grading without Segmentation Maps
por: Ouan, Kim, et al.
Publicado: (2026)

InterTrack: Tracking Human Object Interaction without Object Templates
por: Xie, Xianghui, et al.
Publicado: (2024)

Self-Supervised Learning for Image Segmentation: A Comprehensive Survey
por: Akilan, Thangarajah, et al.
Publicado: (2025)

LIDARLearn: A Unified Deep Learning Library for 3D Point Cloud Classification, Segmentation, and Self-Supervised Representation Learning
por: Ohamouddou, Said, et al.
Publicado: (2026)

PM-VIS+: High-Performance Video Instance Segmentation without Video Annotation
por: Yang, Zhangjing, et al.
Publicado: (2024)

Towards Real Zero-Shot Camouflaged Object Segmentation without Camouflaged Annotations
por: Lei, Cheng, et al.
Publicado: (2024)

Collecting Consistently High Quality Object Tracks with Minimal Human Involvement by Using Self-Supervised Learning to Detect Tracker Errors
por: Anjum, Samreen, et al.
Publicado: (2024)

Self Supervised Deep Learning for Robot Grasping
por: Saqib, Danyal, et al.
Publicado: (2024)

Trashbusters: Deep Learning Approach for Litter Detection and Tracking
por: Jain, Kashish, et al.
Publicado: (2024)

Annolid: Annotate, Segment, and Track Anything You Need
por: Yang, Chen, et al.
Publicado: (2024)

MSSSeg: Learning Multi-Scale Structural Complexity for Self-Supervised Segmentation
por: Li, Haotang, et al.
Publicado: (2025)

Scale-Aware Self-Supervised Learning for Segmentation of Small and Sparse Structures
por: Quesada, Jorge, et al.
Publicado: (2026)

Weakly-Supervised Cross-Domain Segmentation of Electron Microscopy with Sparse Point Annotation
por: Qiu, Dafei, et al.
Publicado: (2024)