9 citations · 9 across the 8 of their papers we have counts for
9 papers
Benchmarking Vision-Language Models for Microscopic Plant Image Understanding
Tianqi Wei, Xin Yu, Zhi Chen +2
Microscopic imaging provides essential visual evidence for studying plant biology and pathology at the cellular and subcellular levels. However, existing benchmarks on vision-langu…
Learning to Synergize Semantic and Geometric Priors for Limited-Data Wheat Disease Segmentation
Shijie Wang, Zijian Wang, Yadan Luo +3
Wheat disease segmentation is fundamental to precision agriculture but faces severe challenges from significant intra-class temporal variations across growth stages. Such substanti…
StomataSeg: Semi-Supervised Instance Segmentation for Sorghum Stomatal Components
Zhongtian Huang, Zhi Chen, Zi Huang +8
Sorghum is a globally important cereal grown widely in water-limited and stress-prone regions. Its strong drought tolerance makes it a priority crop for climate-resilient agricultu…
Dynamic Orchestration of Multi-Agent System for Real-World Multi-Image Agricultural VQA
Yan Ke, Xin Yu, Heming Du +2
Agricultural visual question answering is essential for providing farmers and researchers with accurate and timely knowledge. However, many existing approaches are predominantly de…
Augment to Segment: Tackling Pixel-Level Imbalance in Wheat Disease and Pest Segmentation
Tianqi Wei, Xin Yu, Zhi Chen +2
Accurate segmentation of foliar diseases and insect damage in wheat is crucial for effective crop management and disease control. However, the insect damage typically occupies only…
Track Any Peppers: Weakly Supervised Sweet Pepper Tracking Using VLMs
Jia Syuen Lim, Yadan Luo, Zhi Chen +3
In the Detection and Multi-Object Tracking of Sweet Peppers Challenge, we present Track Any Peppers (TAP) - a weakly supervised ensemble technique for sweet peppers tracking. TAP l…
CF-PRNet: Coarse-to-Fine Prototype Refining Network for Point Cloud Completion and Reconstruction
Zhi Chen, Tianqi Wei, Zecheng Zhao +6
In modern agriculture, precise monitoring of plants and fruits is crucial for tasks such as high-throughput phenotyping and automated harvesting. This paper addresses the challenge…
PlantSeg: A Large-Scale In-the-wild Dataset for Plant Disease Segmentation
Tianqi Wei, Zhi Chen, Xin Yu +3
Plant diseases pose significant threats to agriculture. It necessitates proper diagnosis and effective treatment to safeguard crop yields. To automate the diagnosis process, image…
Divide and Ensemble: Progressively Learning for the Unknown
Hu Zhang, Xin Shen, Heming Du +10
In the wheat nutrient deficiencies classification challenge, we present the DividE and EnseMble (DEEM) method for progressive test data predictions. We find that (1) test images ar…