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Found 7 papers, 3 papers with code
Agriculture-Vision Challenge 2022 -- The Runner-Up Solution for Agricultural Pattern Recognition via Transformer-based Models
The Agriculture-Vision Challenge in CVPR is one of the most famous and competitive challenges for global researchers to break the boundary between computer vision and agriculture sectors, aiming at agricultural pattern recognition from aerial images.
Unbiased Math Word Problems Benchmark for Mitigating Solving Bias
However, current solvers exist solving bias which consists of data bias and learning bias due to biased dataset and improper training strategy.
LogicSolver: Towards Interpretable Math Word Problem Solving with Logical Prompt-enhanced Learning
To address this issue and make a step towards interpretable MWP solving, we first construct a high-quality MWP dataset named InterMWP which consists of 11, 495 MWPs and annotates interpretable logical formulas based on algebraic knowledge as the grounded linguistic logic of each solution equation.
Leveraging Large-Scale Weakly Labeled Data for Semi-Supervised Mass Detection in Mammograms
Starting with a fully supervised model trained on the data with pixel-level masks, the proposed framework iteratively refines the model itself using the entire weakly labeled data (image-level soft label) in a self-training fashion.
Spectral Roll-off Points Variations: Exploring Useful Information in Feature Maps by Its Variations
The variations of SROP is synchronizes with UI variations in various randomized and sufficiently trained model structures.
Prior Guided Feature Enrichment Network for Few-Shot Segmentation
It consists of novel designs of (1) a training-free prior mask generation method that not only retains generalization power but also improves model performance and (2) Feature Enrichment Module (FEM) that overcomes spatial inconsistency by adaptively enriching query features with support features and prior masks.
Ranked #46 on
Few-Shot Semantic Segmentation
on COCO-20i (1-shot)
2D Attentional Irregular Scene Text Recognizer
Irregular scene text, which has complex layout in 2D space, is challenging to most previous scene text recognizers.
