A Seamless Deep Learning Approach for Apple Detection, Depth Estimation, and Tracking Using YOLO Models Enhanced by Multi-Head Attention Mechanism

A Seamless Deep Learning Approach for Apple Detection, Depth Estimation, and Tracking Using YOLO Models Enhanced by Multi-Head Attention Mechanism

Considering precision agriculture, recent technological developments have sparked the emergence of several new tools that can help to automate the agricultural process. For instance, accurately detecting and counting apples in orchards is essential for maximizing harvests and ensuring effective reso...

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Bibliographic Details
Main Authors: Praveen Kumar Sekharamantry, Farid Melgani, Jonni Malacarne, Riccardo Ricci, Rodrigo de Almeida Silva, Jose Marcato Junior
Format: Article
Language:English
Published: MDPI AG 2024-03-01
Series:Computers
Subjects:
apple detection
depth estimation
multi-head attention mechanism
ByteTrack
Online Access:https://www.mdpi.com/2073-431X/13/3/83

Internet

https://www.mdpi.com/2073-431X/13/3/83

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