In this paper, we propose a privacy-preserving semantic segmentation method that uses
encrypted images and models with the vision transformer (ViT), called the segmentation …

In this paper, we propose a combined use of transformed images and vision transformer
(ViT) models transformed with a secret key. We show for the first time that models trained …

With the development of cloud services and machine learning, there has been an inevitable
need to enhance privacy and security when serving video recognition models. Although …

In this paper, we propose a privacy-preserving image classification method using block-wise
scrambled images and a modified ConvMixer. Conventional block-wise scrambled …

Agriculture is considered the backbone of Tanzania's economy, with more than 60% of the
residents depending on it for survival. Maize is the country's dominant and primary food …

Federated learning (FL) is an effective technique for image classification in consumer
electronics. This paper proposes a new FL algorithm called FedHLC to address …

Feature extraction from perturbed images is essential for both privacy protection and pattern
recognition. Traditional CNNs struggle with large-scale spatial perturbations due to their …

In this paper, we propose a novel attack on image encryption for privacy-preserving deep
neural networks (DNNs). Although several encryption schemes have been proposed for …

In this paper, we propose a novel generative model-based attack on learnable image
encryption methods proposed for privacy-preserving deep learning. Various learnable …

Successful transit planning in smart cities requires automated and efficient passenger
counts at the bus stop while also respecting the privacy of passengers-a paramount …