Google Research AI blog

FEBRUARY 17, 2023

However, the vast majority of available training data doesn’t specify what regional variety the translation is in. In light of this data scarcity, we position FRMT as a benchmark for few-shot translation, measuring an MT model’s ability to translate into regional varieties when given no more than 100 labeled examples of each language variety.

Data Scarcity 117

Data Scarcity Computational Linguistics Software Engineer Categorization 117

Pickl AI

OCTOBER 21, 2024

E-commerce E-commerce platforms use ZSL for product categorization and recommendation systems, allowing them to suggest items based on user preferences without requiring exhaustive labelling of all products.

Natural Language Processing 52

Natural Language Processing Data Scarcity Computer Vision Machine Learning 52

Viso.ai

JANUARY 2, 2024

Deep Dive: Convolutional Neural Network Algorithms for Specific Challenges CNNs, while powerful, face distinct challenges in their application, particularly in scenarios like data scarcity, overfitting, and unstructured data environments.

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Computer Vision Data Scarcity 52

Viso.ai

DECEMBER 6, 2023

Image Classification Image classification tasks involve CV models categorizing images into user-defined classes for various applications. Based on the presence of a tiger, the entire image is categorized as such. Semantic Segmentation Semantic segmentation aims to identify each pixel within an image for a more detailed categorization.

Computer Vision 52

Computer Vision Convolutional Neural Networks Neural Network Categorization 52

Viso.ai

JANUARY 16, 2024

Also, you can use N-shot learning models to label data samples with unknown classes and feed the new dataset to supervised learning algorithms for better training. The AI community categorizes N-shot approaches into few, one, and zero-shot learning. Let’s discuss each in more detail.

Neural Network 52

Neural Network Computer Vision Convolutional Neural Networks Algorithm 52

Marktechpost

SEPTEMBER 15, 2024

These sources can be categorized into three types: textual documents (e.g., KD methods can be categorized into white-box and black-box approaches. RAG methods use lightweight retrievers to extract relevant information from various sources, effectively reducing hallucinations in generated content.

BERT 117

BERT LLM Large Language Models Categorization 117