Data-driven models for predicting community changes in freshwater ecosystems: A review

DY Lee, DS Lee, YK Cha, JH Min, YS Park - Ecological Informatics, 2023 - Elsevier
Freshwater ecosystems are sensitive to disturbances related to human activities, such as
climate and land-use changes. To predict and understand the potential impacts of these …

A field weed density evaluation method based on uav imaging and modified u-net

K Zou, X Chen, F Zhang, H Zhou, C Zhang - Remote Sensing, 2021 - mdpi.com
Weeds are one of the main factors affecting the yield and quality of agricultural products.
Accurate evaluation of weed density is of great significance for field management, especially …

[HTML][HTML] Butterfly detection and classification techniques: A review

R Yasmin, A Das, LJ Rozario, ME Islam - Intelligent Systems with …, 2023 - Elsevier
Automatic identification of insects from images is gaining interest and popularity day by day.
Several methods and systems were developed to identify insects accurately. Among all the …

[PDF][PDF] Artificial intelligence in agriculture

B Singh, DP Dhinakaran, C Vijai… - Journal of Survey …, 2023 - sifisheriessciences.com
Artificial Intelligence in Agriculture Page 1 Journal of Survey in Fisheries Sciences 10(3S)
6601-6611 2023 6601 Artificial Intelligence in Agriculture Barinderjit Singh Assistant …

Segmentation of Tuta Absoluta's Damage on Tomato Plants: A Computer Vision Approach

LK Loyani, K Bradshaw, D Machuve - Applied artificial intelligence, 2021 - Taylor & Francis
Tuta absoluta is a major threat to tomato production, causing losses ranging from 80% to
100% when not properly managed. Early detection of T. absoluta's effects on tomato plants …

An empirical study on ensemble of segmentation approaches

L Nanni, A Lumini, A Loreggia, A Formaggio, D Cuza - Signals, 2022 - mdpi.com
Recognizing objects in images requires complex skills that involve knowledge about the
context and the ability to identify the borders of the objects. In computer vision, this task is …

[HTML][HTML] Semantic segmentation of in-field cotton bolls from the sky using deep convolutional neural networks

N Singh, VK Tewari, PK Biswas, LK Dhruw… - Smart Agricultural …, 2022 - Elsevier
Manually picking of cotton bolls is a tedious, costly, and labor-intensive task, while
harvesting using machines results in higher harvesting losses. By keeping selective picking …

Non-destructive robotic sorting of cracked pistachio using deep learning

AE Karadağ, A Kılıç - Postharvest Biology and Technology, 2023 - Elsevier
Pistachio, an agricultural product, is considered one of the guilt-free snacks due to its
nutritional content, taste, and its health benefits. Usually, when it is consumed as a snack, in …

Handling hypercolumn deep features in machine learning for rice leaf disease classification

K Akyol - Multimedia Tools and Applications, 2023 - Springer
Rice leaf disease, which is a plant disease, causes a decrease in rice production and more
importantly, environmental pollution. 10–15% of the losses in rice production are due to rice …

Benchmarking of novel convolutional neural network models for automatic butterfly identification

M Chikkamath, DN Dwivedi, RB Hirekurubar… - Computer Vision and …, 2023 - Springer
Insects represent more than half the living organisms on the earth. Among insects' butterflies
are one of the prominent species. A huge number of butterfly species with various wing …