[HTML][HTML] A decision support system for crop recommendation using machine learning classification algorithms
Today, crop suggestions and necessary guidance have become a regular need for a farmer.
Farmers generally depend on their local agriculture officers regarding this, and it may be …
Farmers generally depend on their local agriculture officers regarding this, and it may be …
Multi-modal LLMs in agriculture: A comprehensive review
Given the rapid emergence and applications of Large Language Models (LLMs) across
various scientific fields, insights regarding their applicability in agriculture are still only …
various scientific fields, insights regarding their applicability in agriculture are still only …
Typography leads semantic diversifying: Amplifying adversarial transferability across multimodal large language models
Recently, Multimodal Large Language Models (MLLMs) achieve remarkable performance in
numerous zero-shot tasks due to their outstanding cross-modal interaction and …
numerous zero-shot tasks due to their outstanding cross-modal interaction and …
Insectmamba: Insect pest classification with state space model
The classification of insect pests is a critical task in agricultural technology, vital for ensuring
food security and environmental sustainability. However, the complexity of pest …
food security and environmental sustainability. However, the complexity of pest …
Enhancing federated semi-supervised learning with out-of-distribution filtering amidst class mismatches
Federated Learning (FL) has gained prominence as a method for training models on edge
computing devices, enabling the preservation of data privacy by eliminating the need to …
computing devices, enabling the preservation of data privacy by eliminating the need to …
Self-adaptive robust motion planning for high dof robot manipulator using deep mpc
Y Zhang, K Mo, F Shen, X Xu, X Zhang… - 2024 3rd International …, 2024 - ieeexplore.ieee.org
In contemporary control theory, self-adaptive methodologies are highly esteemed for their
inherent flexibility and robustness in managing modeling uncertainties. Particularly, robust …
inherent flexibility and robustness in managing modeling uncertainties. Particularly, robust …
Harnessing llms for cross-city od flow prediction
Understanding and predicting Origin-Destination (OD) flows is crucial for urban planning
and transportation management. Traditional OD prediction models, while effective within …
and transportation management. Traditional OD prediction models, while effective within …
Residual-based Language Models are Free Boosters for Biomedical Imaging Tasks
In this study we uncover the unexpected efficacy of residual-based large language models
(LLMs) as part of encoders for biomedical imaging tasks a domain traditionally devoid of …
(LLMs) as part of encoders for biomedical imaging tasks a domain traditionally devoid of …
Deep representation learning for multi-functional degradation modeling of community-dwelling aging population
As the aging population grows, particularly for the baby boomer generation, the United
States is witnessing a significant increase in the elderly population experiencing …
States is witnessing a significant increase in the elderly population experiencing …
Integrating Reinforcement Learning and Large Language Models for Crop Production Process Management Optimization and Control through A New Knowledge …
D Chen, Y Huang - arXiv preprint arXiv:2410.09680, 2024 - arxiv.org
Efficient and sustainable crop production process management is crucial to meet the
growing global demand for food, fuel, and feed while minimizing environmental impacts …
growing global demand for food, fuel, and feed while minimizing environmental impacts …