[HTML][HTML] Machine learning in agriculture domain: A state-of-art survey

V Meshram, K Patil, V Meshram, D Hanchate… - Artificial Intelligence in …, 2021 - Elsevier
Food is considered as a basic need of human being which can be satisfied through farming.
Agriculture not only fulfills humans' basic needs, but also considered as source of …

A survey of deep learning techniques for weed detection from images

ASMM Hasan, F Sohel, D Diepeveen, H Laga… - … and Electronics in …, 2021 - Elsevier
The rapid advances in Deep Learning (DL) techniques have enabled rapid detection,
localisation, and recognition of objects from images or videos. DL techniques are now being …

Automation in agriculture by machine and deep learning techniques: A review of recent developments

MH Saleem, J Potgieter, KM Arif - Precision Agriculture, 2021 - Springer
Recently, agriculture has gained much attention regarding automation by artificial
intelligence techniques and robotic systems. Particularly, with the advancements in machine …

Convolutional neural networks in detection of plant leaf diseases: A review

B Tugrul, E Elfatimi, R Eryigit - Agriculture, 2022 - mdpi.com
Rapid improvements in deep learning (DL) techniques have made it possible to detect and
recognize objects from images. DL approaches have recently entered various agricultural …

Transformer neural network for weed and crop classification of high resolution UAV images

R Reedha, E Dericquebourg, R Canals, A Hafiane - Remote Sensing, 2022 - mdpi.com
Monitoring crops and weeds is a major challenge in agriculture and food production today.
Weeds compete directly with crops for moisture, nutrients, and sunlight. They therefore have …

Computer vision with deep learning for plant phenotyping in agriculture: A survey

AL Chandra, SV Desai, W Guo… - arXiv preprint arXiv …, 2020 - arxiv.org
In light of growing challenges in agriculture with ever growing food demand across the
world, efficient crop management techniques are necessary to increase crop yield. Precision …

[HTML][HTML] Dataset of annotated food crops and weed images for robotic computer vision control

K Sudars, J Jasko, I Namatevs, L Ozola, N Badaukis - Data in brief, 2020 - Elsevier
Weed management technologies that can identify weeds and distinguish them from crops
are in need of artificial intelligence solutions based on a computer vision approach, to …

A survey on deep learning and its impact on agriculture: Challenges and opportunities

M Albahar - Agriculture, 2023 - mdpi.com
The objective of this study was to provide a comprehensive overview of the recent
advancements in the use of deep learning (DL) in the agricultural sector. The author …

Weed recognition using deep learning techniques on class-imbalanced imagery

ASMM Hasan, F Sohel, D Diepeveen… - Crop and Pasture …, 2022 - CSIRO Publishing
Context Most weed species can adversely impact agricultural productivity by competing for
nutrients required by high-value crops. Manual weeding is not practical for large cropping …

Application of deep learning with stratified K-fold for vegetation species discrimation in a protected mountainous region using Sentinel-2 image

EG Adagbasa, SA Adelabu, TW Okello - Geocarto International, 2022 - Taylor & Francis
Understanding the spatial distribution of vegetation species is essential to gain knowledge
on the recovery process of an ecosystem. Few studies have used deep learning and …