Abstract: The effectiveness and robustness of medical image segmentation algorithms inextricably depends on the quality and quantity of training data. Insufficient data continually restricts model ...

AI data trainers who ensure the accuracy and viability of training data going into AI models are well-compensated, in-demand professionals. Two new studies projected potential annual incomes ranging ...

Introduction Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in ...

Abstract: The study presents a methodology for automatically creating an annotated dataset for further use in training neural networks. The method is based on the Crisp-DM framework and consists of 6 ...

Overview: Matplotlib mistakes often come from poor layout, unclear labels, and wrong scale choices, not from the data ...

Bridging communication gaps between hearing and hearing-impaired individuals is an important challenge in assistive ...

Python gives you far more control, and the ecosystem is stacked with libraries that can replace most no-code platforms if you ...

Meta’s most popular LLM series is Llama. Llama stands for Large Language Model Meta AI. They are open-source models. Llama 3 was trained with fifteen trillion tokens. It has a context window size of ...

The Git-10M dataset is a global-scale dataset, consisting of 10.5 million image-text pairs with geographical locations and resolution information. You can skip the following steps if you have higher ...

We propose a synthetic data generation and annotation framework that enables panoramic object detection using existing large-scale planar image datasets. Instead of relying solely on limited ...