Results 51 to 60 of about 18,617 (276)
Frontiers in OncologyCervical cancer is a prevalent and concerning disease affecting women, with increasing incidence and mortality rates. Early detection plays a crucial role in improving outcomes.
Manal Abdullah Alohali +7 more
doaj +1 more source
Inspecting Explainability of Transformer Models with Additional Statistical Information
, 2023 Transformer becomes more popular in the vision domain in recent years so there is a need for finding an effective way to interpret the Transformer model by visualizing it. In recent work, Chefer et al.
Kim, Junmo, Lee, Haeil, Nguyen, Hoang C.
core
When Biology Meets Medicine: A Perspective on Foundation Models
Advanced Intelligent Discovery, EarlyView.Artificial intelligence, and foundation models in particular, are transforming life sciences and medicine. This perspective reviews biological and medical foundation models across scales, highlighting key challenges in data availability, model evaluation, and architectural design.
Kunying Niu +3 more
wiley +1 more source
, 2023 Accurately predicting the destination of taxi trajectories can have various benefits for intelligent location-based services. One potential method to accomplish this prediction is by converting the taxi trajectory into a two-dimensional grid and using ...
Lei, Zhiyu +4 more
core
BMPCQA: Bioinspired Metaverse Point Cloud Quality Assessment Based on Large Multimodal Models
Advanced Intelligent Systems, EarlyView.This study presents a bioinspired metaverse point cloud quality assessment metric, which simulates the human visual evaluation process to perform the point cloud quality assessment task. It first extracts rendering projection video features, normal image features, and point cloud patch features, which are then fed into a large multimodal model to ...
Huiyu Duan +7 more
wiley +1 more source
Deep Reinforcement Learning with Swin Transformers
Proceedings of the 2024 8th International Conference on Digital Signal ProcessingTransformers are neural network models that utilize multiple layers of self-attention heads and have exhibited enormous potential in natural language processing tasks. Meanwhile, there have been efforts to adapt transformers to visual tasks of machine learning, including Vision Transformers and Swin Transformers.
Li Meng +3 more
openaire +2 more sources
Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Images
, 2022 13 pages, 3 ...
Ali Hatamizadeh +5 more
openaire +2 more sources
Brain Tumor Detection using Swin Transformers
CoRR, 2023 The first MRI scan was done in the year 1978 by researchers at EML Laboratories. As per an estimate, approximately 251,329 people died due to primary cancerous brain and CNS (Central Nervous System) Tumors in the year 2020. It has been recommended by various medical professionals that brain tumor detection at an early stage would help in saving many ...
Prateek A. Meshram +2 more
openaire +2 more sources
Advanced Intelligent Systems, EarlyView.A zero‐watermarking algorithm that combines a refined convolutional additive self‐attention vision transformer (CAS‐ViT) with a discrete wavelet transform variance‐based feature descriptor (DVFD) is proposed for protecting the privacy of medical images in mobile healthcare services.
Pei Liu +6 more
wiley +1 more source
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022 Easy and efficient acquisition of high-resolution remote sensing images is of importance in geographic information systems. Previously, deep neural networks composed of convolutional layers have achieved impressive progress in super-resolution ...
Jingzhi Tu +3 more
doaj +1 more source