IRPruneDet: Efficient Infrared Small Target Detection via Wavelet Structure-Regularized Soft Channel Pruning
Authors: Mingjin Zhang, Handi Yang, Jie Guo, Yunsong Li, Xinbo Gao, Jing Zhang
AAAI 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Through extensive experiments on two widely-used benchmarks, our IRPrune Det method surpasses established techniques in both model complexity and accuracy. |
| Researcher Affiliation | Academia | Mingjin Zhang1, Handi Yang1*, Jie Guo1, Yunsong Li1, Xinbo Gao1, Jing Zhang2* 1Xidian University 2The University of Sydney |
| Pseudocode | No | The paper does not contain any structured pseudocode or algorithm blocks clearly labeled as such. |
| Open Source Code | Yes | The code is available at https://github.com/hd0013/IRPrune Det. |
| Open Datasets | Yes | We adopt the NUAA-SIRST (Dai et al. 2021a) and IRSTD-1k (Zhang et al. 2022c) datasets for evaluation. |
| Dataset Splits | Yes | For each dataset, we divide IR images into three disjoint subsets: 50% for training, 30% for validation, and 20% for testing. |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., GPU/CPU models, memory amounts) used for running its experiments. It only mentions general terms like 'platforms with limited resources' or 'general-purpose hardware' in a theoretical context. |
| Software Dependencies | No | The paper mentions 'Ada Grad as the optimizer' but does not provide specific version numbers for any software dependencies or libraries used for the experiments. |
| Experiment Setup | Yes | We resize the size of each IR image in NUAA-SIRST and IRSTD-1k datasets to 512 × 512... For the pruning and training process, we utilize Ada Grad as the optimizer with a learning rate of 0.01. The training process lasts for 500 epochs with a weight decay of 10−4 and a batch size of 16. By default, we set βSCR to 0.5π and β0 to 1. We apply IRPrune Det only to a U-Net18 baseline model |