Visual Tactile Fusion Object Clustering
Authors: Tao Zhang, Yang Cong, Gan Sun, Qianqian Wang, Zhenming Ding10426-10433
AAAI 2020 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Finally, we conduct extensive experiments on public datasets to verify the effectiveness of our framework. ... In this section, we evaluate the performance of our proposed model via several empirical comparisons. We first provide the used datasets and experiment results, followed by some analyses about our model. |
| Researcher Affiliation | Academia | 1State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences 2University of Chinese Academy of Sciences, 3Xidian University, 4Indiana University-Purdue University Indianapolis, USA |
| Pseudocode | Yes | Algorithm 1 Optimization of Problem (4) |
| Open Source Code | No | The paper provides links to datasets used but does not include a statement or link for the source code of their proposed method. |
| Open Datasets | Yes | PHAC-2 dataset: http://people.eecs.berkeley.edu/ yg/icra2016 Gel Fold Fabric dataset: http://people.csail.mit.edu/yuan wz/fabric-perception.htm Yale dataset: http://vision.ucsd.edu/content/yale-face-database |
| Dataset Splits | No | The paper describes the datasets used but does not explicitly provide information on how they were split into training, validation, or test sets (e.g., percentages or specific counts for each split). |
| Hardware Specification | No | The paper does not provide any specific details about the hardware (e.g., CPU, GPU models, memory) used for running the experiments. |
| Software Dependencies | No | The paper mentions using a "pre-trained VGG-19 net" and extracting features, but it does not specify software dependencies with version numbers (e.g., specific deep learning frameworks like PyTorch or TensorFlow, or their versions). |
| Experiment Setup | Yes | For avoiding overfitting, the maximum number of iterations is set to 150 for all experiments. ... when β is set as 0.01. We thus set β = 0.01 as default in this paper. ... when λ is set as 0.01. So λ = 0.01 is set as default. ... the setting of [500, 50] always leads to best performance. |