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Retail Product Recognition: A Combination of Yolov8 and Modified Self-Supervised Learning

https://doi.org/10.2139/ssrn.4890491
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inferredcites →https://doi.org/10.1002/tee.23051openalex-extracted
TemplateFree: product detection on retail store shelves
inferredcites →https://doi.org/10.1007/s11042-023-15633-1openalex-extracted
Product identification in retail stores by combining faster r-cnn and recurrent neural network
inferredcites →https://doi.org/10.1007/s42001-024-00266-7openalex-extracted
Efficient annotation reduction with active learning for computer vision-based Retail Product Recognition
inferredcites →https://doi.org/10.1016/j.neucom.2024.127685openalex-extracted
Multi-YOLOv8: An infrared moving small object detection model based on YOLOv8 for air vehicle
inferredcites →https://doi.org/10.1016/j.patrec.2024.09.005openalex-extracted
DeepSet SimCLR: Self-supervised deep sets for improved pathology representation learning
inferredcites →https://doi.org/10.1038/s41586-023-05732-2openalex-extracted
Dense reinforcement learning for safety validation of autonomous vehicles
inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-extracted
Deep Residual Learning for Image Recognition
inferredcites →https://doi.org/10.1109/iccv.2015.170openalex-extracted
Bilinear CNN Models for Fine-Grained Visual Recognition
inferredcites →https://doi.org/10.1109/ssci50451.2021.9659998openalex-extracted
Classification of Seeds using Domain Randomization on Self-Supervised Learning Frameworks
inferredcites →https://doi.org/10.1109/tsmc.2022.3166397openalex-extracted
Computer Vision Techniques in Manufacturing
inferredcites →https://doi.org/10.1109/wacv.2019.00058openalex-extracted
A Hierarchical Grocery Store Image Dataset With Visual and Semantic Labels
inferredcites →https://doi.org/10.1109/wacv57701.2024.00677openalex-extracted
MotionAGFormer: Enhancing 3D Human Pose Estimation with a Transformer-GCNFormer Network
inferredcites →https://doi.org/10.1134/s105466182104012xopenalex-extracted
Retail Product Classification on Distinct Distribution of Training and Evaluation Data
inferredcites →https://doi.org/10.1145/3065386openalex-extracted
ImageNet classification with deep convolutional neural networks
inferredcites →https://doi.org/10.1155/2020/8875910openalex-extracted
Deep Learning for Retail Product Recognition: Challenges and Techniques
inferredcites →https://doi.org/10.31436/ijpcc.v10i1.460openalex-extracted
Utilising VGG-16 of Convolutional Neural Network for Medical Image Classification
inferredcites →https://doi.org/10.32604/iasc.2022.017706openalex-extracted
Plant Disease Classification Using Deep Bilinear CNN
inferredcites →https://doi.org/10.3390/app12147255openalex-extracted
Improved YOLOv5: Efficient Object Detection Using Drone Images under Various Conditions
inferredcites →https://doi.org/10.3390/cancers15164172openalex-extracted
Brain Tumor Detection Based on Deep Learning Approaches and Magnetic Resonance Imaging
inferredcites →https://doi.org/10.3390/make5040083openalex-extracted
A Comprehensive Review of YOLO Architectures in Computer Vision: From YOLOv1 to YOLOv8 and YOLO-NAS
inferredcites →https://doi.org/10.3390/s21155116openalex-extracted
Survey and Performance Analysis of Deep Learning Based Object Detection in Challenging Environments
inferredcites →https://doi.org/10.48550/arxiv.1409.1556openalex-extracted
Very Deep Convolutional Networks for Large-Scale Image Recognition
inferredcites →https://doi.org/10.48550/arxiv.2002.05709openalex-extracted
A Simple Framework for Contrastive Learning of Visual Representations
inferredcites →https://doi.org/10.48550/arxiv.2108.00587openalex-extracted
Semi-Supervising Learning, Transfer Learning, and Knowledge Distillation with SimCLR
inferredcites →https://doi.org/10.48550/arxiv.2305.09972openalex-extracted
Real-Time Flying Object Detection with YOLOv8
inferredcites →https://doi.org/10.54097/39xpbb68openalex-extracted
Improve Unsupervised Machine Learning Model on Fruits by Using VGG-16
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