activity
20182022
most citedDiscriminative Latent Semantic Graph for Video Captioning

26 citations · 44 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV202310 cited

Identifying the Defective: Detecting Damaged Grains for Cereal Appearance Inspection

Lei Fan, Yiwen Ding, Dongdong Fan +3

Cereal grain plays a crucial role in the human diet as a major source of essential nutrients. Grain Appearance Inspection (GAI) serves as an essential process to determine grain qu…

cs.LG202216 cited

Explainability in Graph Neural Networks: An Experimental Survey

Peibo Li, Yixing Yang, Maurice Pagnucco +1

Graph neural networks (GNNs) have been extensively developed for graph representation learning in various application domains. However, similar to all other neural networks models,…

cs.CV20222 cited

GrainSpace: A Large-scale Dataset for Fine-grained and Domain-adaptive Recognition of Cereal Grains

Lei Fan, Yiwen Ding, Dongdong Fan +3

Cereal grains are a vital part of human diets and are important commodities for people's livelihood and international trade. Grain Appearance Inspection (GAI) serves as one of the…

cs.CV202126 cited

Discriminative Latent Semantic Graph for Video Captioning

Yang Bai, Junyan Wang, Yang Long +4

Video captioning aims to automatically generate natural language sentences that can describe the visual contents of a given video. Existing generative models like encoder-decoder f…

cs.AI2018

Perceptual Context in Cognitive Hierarchies

Bernhard Hengst, Maurice Pagnucco, David Rajaratnam +2

Cognition does not only depend on bottom-up sensor feature abstraction, but also relies on contextual information being passed top-down. Context is higher level information that he…