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Bigger models, more parameters, higher benchmarks. There is often a fixation on scale in the discourse around AI, making it easy to assume that the bigger a Large Language Model (LLM) is, the better ...
Abstract: Identifying damage processes in carbon fiber-reinforced polymer (CFRP) is critical for inspection. Existing detection methods primarily rely on single-sensor techniques, which often fail to ...
Abstract: More and more complex and numerous are the forensic findings required while investigating the crime scene, it is important to address the need for technological enhancements for the crime ...
Abstract: Potato crops are vital to global food security, but they are susceptible to several diseases that hinder growth and yield. Traditional methods of detecting these diseases rely on ...
Abstract: The health of marine species in aquaculture depends on maintaining ideal water quality. Conventional biofloc monitoring techniques are time-consuming and do not respond in real time. In ...
Abstract: This study investigates the vulnerability of Convolutional Neural Network (CNN) models to adversarial attacks, focusing on the Fast Gradient Sign Method (FGSM). We implemented and compared ...
Abstract: A wireless body area network (WBAN) is a crucial technology for implementing intelligent health monitoring. Traditional WBANs focus on the monitoring and classification of single ...
Abstract: It is a neurodegenerative disorder wherein the cognitive function is drastically affected, particularly in aging populations. An early and definitive diagnosis ensures an appropriate ...
A Hybrid 3D CNN and Artificial Ecosystem-based Optimization (AEO) Model for Thyroid Nodule Detection
Abstract: Generally, doctors frequently require sophisticated diagnostic equipment to identify and do follow-up diagnoses on thyroid nodules. They spend a long time manually extracting features from ...
Abstract: This study presents a combined method that improves the ability to predict and understand outcomes by merging Convolutional Neural Networks (CNN) with Explainable Artificial Intelligence ...
Abstract: The mitigation of crop losses and the sustainability of agriculture rely on the prompt identification of foliar diseases. In large-scale agriculture, conventional identification methods such ...
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