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Found 7 papers, 5 papers with code
Crowdsource, Crawl, or Generate? Creating SEA-VL, a Multicultural Vision-Language Dataset for Southeast Asia
Beyond crowdsourcing, our initiative goes one step further in the exploration of the automatic collection of culturally relevant images through crawling and image generation.
Barking Up The Syntactic Tree: Enhancing VLM Training with Syntactic Losses
Vision-Language Models (VLMs) implicitly learn to associate image regions with words from large-scale training data, demonstrating an emergent capability for grounding concepts without dense annotations[14, 18, 51].
Emergent Open-Vocabulary Semantic Segmentation from Off-the-shelf Vision-Language Models
From image-text pairs, large-scale vision-language models (VLMs) learn to implicitly associate image regions with words, which prove effective for tasks like visual question answering.
A Survey of Computer Vision Technologies In Urban and Controlled-environment Agriculture
In addition, we discuss five key subareas of computer vision and how they related to these CEA problems, as well as eleven vision-based CEA datasets.
An Evaluation of Machine Learning and Deep Learning Models for Drought Prediction using Weather Data
While this problem has been studied in the literature, it remains unknown whether drought can be precisely predicted or not with machine learning models using weather data.
Big Data for Traffic Estimation and Prediction: A Survey of Data and Tools
Big data has been used widely in many areas including the transportation industry.
Graph Neural Network for Traffic Forecasting: A Survey
In recent years, to model the graph structures in transportation systems as well as contextual information, graph neural networks have been introduced and have achieved state-of-the-art performance in a series of traffic forecasting problems.
