Expanding the horizons of machine learning in nanomaterials to chiral nanostructures
V Kuznetsova, Á Coogan, D Botov… - Advanced …, 2024 - Wiley Online Library
Abstract Machine learning holds significant research potential in the field of nanotechnology,
enabling nanomaterial structure and property predictions, facilitating materials design and …
enabling nanomaterial structure and property predictions, facilitating materials design and …
A survey of the vision transformers and their CNN-transformer based variants
Vision transformers have become popular as a possible substitute to convolutional neural
networks (CNNs) for a variety of computer vision applications. These transformers, with their …
networks (CNNs) for a variety of computer vision applications. These transformers, with their …
Gridformer: Residual dense transformer with grid structure for image restoration in adverse weather conditions
Image restoration in adverse weather conditions is a difficult task in computer vision. In this
paper, we propose a novel transformer-based framework called GridFormer which serves as …
paper, we propose a novel transformer-based framework called GridFormer which serves as …
[HTML][HTML] DiffPlate: A Diffusion Model for Super-Resolution of License Plate Images
License plate recognition is a pivotal challenge in surveillance applications, predominantly
due to the low resolution and diminutive size of license plates, which impairs recognition …
due to the low resolution and diminutive size of license plates, which impairs recognition …
Single image super-resolution approaches in medical images based-deep learning: a survey
Abstract Medical image Super-Resolution (SR) reconstruction refers to the process of
regenerating a High-Resolution (HR) image from a degraded Low-Resolution (LR) image or …
regenerating a High-Resolution (HR) image from a degraded Low-Resolution (LR) image or …
Harmony in diversity: Improving all-in-one image restoration via multi-task collaboration
Deep learning-based all-in-one image restoration methods have garnered significant
attention in recent years due to capable of addressing multiple degradation tasks. These …
attention in recent years due to capable of addressing multiple degradation tasks. These …
Self-Supervised Learning for Text Recognition: A Critical Survey
C Penarrubia, JJ Valero-Mas… - arXiv preprint arXiv …, 2024 - arxiv.org
Text Recognition (TR) refers to the research area that focuses on retrieving textual
information from images, a topic that has seen significant advancements in the last decade …
information from images, a topic that has seen significant advancements in the last decade …
Non-small cell lung cancer detection through knowledge distillation approach with teaching assistant
Non-small cell lung cancer (NSCLC) exhibits a comparatively slower rate of metastasis in
contrast to small cell lung cancer, contributing to approximately 85% of the global patient …
contrast to small cell lung cancer, contributing to approximately 85% of the global patient …
Revolutionizing dementia detection: Leveraging vision and Swin transformers for early diagnosis
Dementia, an increasingly prevalent neurological disorder with a projected threefold rise
globally by 2050, necessitates early detection for effective management. The risk notably …
globally by 2050, necessitates early detection for effective management. The risk notably …
MACGAN: an all-in-one image restoration under adverse conditions using multidomain attention-based conditional GAN
Various vision-based tasks suffer from inaccurate navigation and poor performance due to
inevitable problems, such as adverse weather conditions like haze, fog, rain, snow, and …
inevitable problems, such as adverse weather conditions like haze, fog, rain, snow, and …