activity
20232025
most citedIdentifying the Defective: Detecting Damaged Grains for Cereal Appearance Inspection

10 citations · 10 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV2025

Prototype-Based Image Prompting for Weakly Supervised Histopathological Image Segmentation

Qingchen Tang, Lei Fan, Maurice Pagnucco +1

Weakly supervised image segmentation with image-level labels has drawn attention due to the high cost of pixel-level annotations. Traditional methods using Class Activation Maps (C…

cs.CV2025

Interpretable Image Classification via Non-parametric Part Prototype Learning

Zhijie Zhu, Lei Fan, Maurice Pagnucco +1

Classifying images with an interpretable decision-making process is a long-standing problem in computer vision. In recent years, Prototypical Part Networks has gained traction as a…

cs.CV2024

MANTA: A Large-Scale Multi-View and Visual-Text Anomaly Detection Dataset for Tiny Objects

Lei Fan, Dongdong Fan, Zhiguang Hu +5

We present MANTA, a visual-text anomaly detection dataset for tiny objects. The visual component comprises over 137.3K images across 38 object categories spanning five typical doma…

cs.CV2024

Salvaging the Overlooked: Leveraging Class-Aware Contrastive Learning for Multi-Class Anomaly Detection

Lei Fan, Junjie Huang, Donglin Di +4

For anomaly detection (AD), early approaches often train separate models for individual classes, yielding high performance but posing challenges in scalability and resource managem…

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…