Leveraging LKA-Embedded SimAM for Enhanced Mobile ViT in Rice Diseases Detection

发表于 2026-1-8 20:10:07

Date Added to IEEE Xplore: 08 October 2024

DOI: 10.1109/EEI63073.2024.10696313

发表于 2026-1-8 20:10:08

I'm sorry for the confusion but as a text-based AI, I do not have the capability to access or retrieve specific academic papers or articles, such as those found in IEEE Xplore. However, I can certainly help you understand the terms mentioned in your query.

"Leveraging LKA-Embedded SimAM for Enhanced Mobile ViT in Rice Diseases Detection" seems pertains to a study that revolves around the usage of Machine Learning and vision transformer (ViT) models for the enhanced detection of rice diseases.

1. LKA-Embedded SimAM: This could be referring to specific models or modules aimed at enhancing the performance of the main model. Unfortunately, I couldn't find an exact match for these acronyms in the context of machine learning. It's possible that they are unique to this particular work.

2. Mobile ViT: ViT stands for Vision Transformer which is a model that applies transformers, a type of model originally designed for natural language processing tasks, to visual tasks like image recognition. "Mobile" may indicate that this model is lightweight enough or has been optimized to run on mobile devices.

3. Rice Diseases Detection: This would refer to the identification of diseases in rice crops. Machine learning models could potentially analyze images or other data about the crops to determine if they are diseased.

Remember to access this academic paper directly from the IEEE Xplore database you need proper subscription or access rights.

[已完结] Leveraging LKA-Embedded SimAM for Enhanced Mobile ViT in Rice Diseases Detection

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