[HTML][HTML] Optimizing tomato plant phenoty** detection: Boosting YOLOv8 architecture to tackle data complexity

F Solimani, A Cardellicchio, G Dimauro… - … and Electronics in …, 2024‏ - Elsevier
Effective identification of tomato plant traits is crucial for timely monitoring and evaluating
their growth and harvest. However, conducting stress experiments on multiple tomato …

Selecting and composing learning rate policies for deep neural networks

Y Wu, L Liu - ACM Transactions on Intelligent Systems and …, 2023‏ - dl.acm.org
The choice of learning rate (LR) functions and policies has evolved from a simple fixed LR to
the decaying LR and the cyclic LR, aiming to improve the accuracy and reduce the training …

Rethinking learning rate tuning in the era of large language models

H **, W Wei, X Wang, W Zhang… - 2023 IEEE 5th …, 2023‏ - ieeexplore.ieee.org
Large Language Models (LLMs) represent the recent success of deep learning in achieving
remarkable human-like predictive performance. It has become a mainstream strategy to …

[HTML][HTML] AI-Powered Cow Detection in Complex Farm Environments

VM Araújo, I Rili, T Gisiger, S Gambs, E Vasseur… - Smart Agricultural …, 2025‏ - Elsevier
Animal welfare has become a critical issue in contemporary society, emphasizing our ethical
responsibilities toward animals, particularly within livestock farming. In addition, the advent …

Chlorophyll a predictions in a Piedmont Lake in Upstate South Carolina using machine-learning approaches

IO Busari, D Sahoo, R Jana… - Journal of South Carolina …, 2023‏ - open.clemson.edu
Freshwater systems are often breeding grounds for harmful algal blooms (HABs), although
they are more dominant in ponds and lakes due to the prevailing conditions in those bodies …

A survey: evolutionary deep learning

Y Li, J Liu - Soft Computing, 2023‏ - Springer
Deep learning (DL) has made remarkable progress on various real-world tasks, but its
construction pipeline strongly relies on human scientists. Furthermore, evolutionary …

Evolving intelligence: Overcoming challenges for Evolutionary Deep Learning

MG Altarabichi - 2024‏ - diva-portal.org
Deep Learning (DL) has achieved remarkable results in both academic and industrial fields
over the last few years. However, DL models are often hard to design and require proper …

Evolving adaptive neural network optimizers for image classification

P Carvalho, N Lourenço, P Machado - European Conference on Genetic …, 2022‏ - Springer
The evolution of hardware has enabled Artificial Neural Networks to become a staple
solution to many modern Artificial Intelligence problems such as natural language …