来自Adobe 和加州伯克利的研究人员在论文预印本平台 arXiv 上传了《CNN-generated images are surprisingly easy to spot... for now》,他们提出,即使是在一种 CNN 生成的图像所训练的分类器,也能够跨数据集、网络架构和训练任务,展现出惊人的泛化能力。这篇论文目前已被 CVPR 2020 接收,代码和模型也已公布。 ...
We perform experimental evaluations on the CNNSpot-DS and GenImage datasets. Experimental results show that our IPD-Net outperforms several state-of-the-art baseline models on multiple metrics and has good generalization ability.Jiahan ChenMengtin Lo...
Detection of AI-Generated Synthetic Images with a Lightweight CNN The rapid development of generative adversarial networks has significantly advanced the generation of synthetic images, presenting valuable opportunities a... D Vlahek - AI 被引量: 0发表: 2024年 Generative AI in orthopedics: an explai...
cnn_model.ipynb: Train and test model using huggingface model on local. mobileNetV2_visual.ipynb: Visualize MobileNetV2 model. resNet_visualization.ipynb & restNet_visual.ipynb: Visualize RestNet50 using UMAP. app.py: deploy the AI generator and detector using huggingface and streamlit. ...
(2020) proposed a TL-CNN based on using a VGG19 pre-trained model to differentiate between wet AMD, GA, drusen, and normal OCT scans. They used a dataset collected from Northwestern Memorial Hospital composed of 396 OCT images for the training set and 102 images for the testing set, ...
Classification of Ear Imagery Database using Bayesian Optimization based on CNN-LSTM Architecture 2022, Journal of Digital Imaging Artificial intelligence to classify ear disease from otoscopy: A systematic review and meta-analysis 2022, Clinical Otolaryngology ...
Our findings indicate that CNN may prove valuable for a computer-aided diagnosis and classification of images generated by medical imaging systems 展开 关键词: epilepsy classification image analysis magnetic resonance imaging 会议名称: International Workshop on Cellular Neural Networks & Their Applications ...
[168] –LightGBM –CNN –Unknown –Not enough information about the datasets used. 2019 Ferdowsi et al. [169] –Distributed GAN –SBHAR [171] –This approach might be prone to iterative generated attacks. 2021 Abdel-Basset et al. [172] –DC-Conv –C-Conv –Attention module –CIC-IDS...
Image data set is classified using the LeNet architecture as a CNN. Results obtained are very promising in the real working conditions in which there were many varying conditions such as illumination, complex background, mixed resolution, size, pose, and orientation of images as expected in ...
Table 5: Number of correct predictions made by CLIP, DIRE, and CNNDet Generation MethodTotal ImagesCNNDETDIRECLIP ADM9783978971 DDPM1037510341034 Diff-ProjectedGAN97744976977 Diff-StyleGAN2100981110091009 IDDPM9864986986 LDM9624962961 PNDM1010210101010