Results 1 to 10 of about 38,761 (113)

Robust Fruit Counting: Combining Deep Learning, Tracking, and Structure from Motion [PDF]

arXiv, 2018
We present a novel fruit counting pipeline that combines deep segmentation, frame to frame tracking, and 3D localization to accurately count visible fruits across a sequence of images. Our pipeline works on image streams from a monocular camera, both in natural light, as well as with controlled illumination at night.
Xu Liu, Steven W. Chen, Shreyas Aditya, Nivedha Sivakumar, Sandeep Dcunha, Chao Qu, Camillo J. Taylor, Jnaneshwar Das, Vijay Kumar   +8 more
arxiv   +4 more sources

FruitNeRF: A Unified Neural Radiance Field based Fruit Counting Framework [PDF]

arXiv
We introduce FruitNeRF, a unified novel fruit counting framework that leverages state-of-the-art view synthesis methods to count any fruit type directly in 3D. Our framework takes an unordered set of posed images captured by a monocular camera and segments fruit in each image.
Lukas Meyer, Andreas Gilson, Ute Schmidt, Marc Stamminger   +3 more
openalex   +2 more sources

Developing Machine Vision in Tree-Fruit Applications—Fruit Count, Fruit Size and Branch Avoidance in Automated Harvesting [PDF]

Sensors
Recent developments in affordable depth imaging hardware and the use of 2D Convolutional Neural Networks (CNN) in object detection and segmentation have accelerated the adoption of machine vision in a range of applications, with mainstream models often ...
Chiranjivi Neupane, Kerry B. Walsh, Rafael Goulart, Anand Koirala   +3 more
doaj   +2 more sources

Monocular Camera Based Fruit Counting and Mapping With Semantic Data Association [PDF]

, 2019
We present a cheap, lightweight, and fast fruit counting pipeline that uses a single monocular camera. Our pipeline that relies only on a monocular camera, achieves counting performance comparable to state-of-the-art fruit counting system that utilizes an expensive sensor suite including LiDAR and GPS/INS on a mango dataset.
Xu Liu, Steven W. Chen, Chenhao Liu, Shreyas S. Shivakumar, Jnaneshwar Das, Camillo J. Taylor, James Underwood, Vijay Kumar   +7 more
openalex   +2 more sources

A comparative study of fruit detection and counting methods for yield mapping in apple orchards [PDF]

, 2019
We present new methods for apple detection and counting based on recent deep learning approaches and compare them with state-of-the-art results based on classical methods. Our goal is to quantify performance improvements by neural network-based methods compared to methods based on classical approaches.
Nicolai Häni, Pravakar Roy, Volkan Isler   +2 more
openalex   +2 more sources

AgRegNet: A Deep Regression Network for Flower and Fruit Density Estimation, Localization, and Counting in Orchards [PDF]

Computers and Electronics in Agriculture 227 (2024): 109534
One of the major challenges for the agricultural industry today is the uncertainty in manual labor availability and the associated cost. Automated flower and fruit density estimation, localization, and counting could help streamline harvesting, yield estimation, and crop-load management strategies such as flower and fruitlet thinning.
Uddhav Bhattarai, Santosh Bhusal, Qin Zhang, Manoj Karkee   +3 more
openalex   +2 more sources

Towards Safe and Efficient Through-the-Canopy Autonomous Fruit Counting with UAVs [PDF]

arXiv
We present an autonomous aerial system for safe and efficient through-the-canopy fruit counting. Aerial robot applications in large-scale orchards face significant challenges due to the complexity of fine-tuning flight paths based on orchard layouts, canopy density, and plant variability.
Teaya Yang, Roman Ibrahimov, Mark W. Mueller   +2 more
openalex   +2 more sources

Short Notes: Application of Vesicular Arbuscular Mycorrhiza: Increasing the Yield of Okra

Maǧallaẗ al-baṣraẗ al-ʻulūm al-zirāʻiyyaẗ, 2023
A commercially available arbuscular mycorrhizal fungi was applied to investigate the response of okra plants, particularly the yield components. Okra plants were separately treated with inorganic fertilizer, organic fertilizer, and mycorrhiza.
Maricar O. Dahilig, Raymund J. G. Rosales   +1 more
doaj   +5 more sources

Attempting to Estimate the Unseen—Correction for Occluded Fruit in Tree Fruit Load Estimation by Machine Vision with Deep Learning

Agronomy, 2021
Machine vision from ground vehicles is being used for estimation of fruit load on trees, but a correction is required for occlusion by foliage or other fruits. This requires a manually estimated factor (the reference method).
Anand Koirala, Kerry B. Walsh, Zhenglin Wang   +2 more
doaj   +1 more source

Evaluation of methods to estimate understory fruit biomass. [PDF]

PLoS ONE, 2014
Fleshy fruit is consumed by many wildlife species and is a critical component of forest ecosystems. Because fruit production may change quickly during forest succession, frequent monitoring of fruit biomass may be needed to better understand shifts in ...
Marcus A Lashley, Jeffrey R Thompson, M Colter Chitwood, Christopher S Deperno, Christopher E Moorman   +4 more
doaj   +1 more source