Results 21 to 30 of about 1,512,599 (152)
Transformer architectures for computer vision: A comprehensive review and future research directions [PDF]
Long-range dependencies and contextual relationships in videos were captured by using Convolutional Neural Networks (CNNs) in past. Recently the use of Transformers is started for capturing the long-range dependencies and contextual relationships in ...
Ugile Tukaram, Uke Nilesh
doaj +1 more source
Transformer-based ripeness segmentation for tomatoes
With the recent development of computer vision technology, various computer vision techniques have been applied to agriculture. Recently, the Transformer network has been introduced to image recognition, which allows a different approach to extracting ...
Risa Shinoda +3 more
doaj +1 more source
Handwritten Text Recognition Using a Vision Transformer
The aim of this project is to create a method for offline handwritten text recognition using a vision transformer. It consists of two parts, where the first one segments all words in a document into separate images and the second one which recognizes the
Kurén, Jonathan, Sundberg, Martin
core +2 more sources
Vision Transformers Are Robust Learners
Transformers, composed of multiple self-attention layers, hold strong promises toward a generic learning primitive applicable to different data modalities, including the recent breakthroughs in computer vision achieving state-of-the-art (SOTA) standard accuracy. What remains largely unexplored is their robustness evaluation and attribution.
Sayak Paul, Pin-Yu Chen
openaire +3 more sources
Art authentication with vision transformers
AbstractIn recent years, transformers, initially developed for language, have been successfully applied to visual tasks. Vision transformers have been shown to push the state of the art in a wide range of tasks, including image classification, object detection, and semantic segmentation.
Schaerf, Ludovica +2 more
openaire +4 more sources
Distinguishing Malicious Drones Using Vision Transformer
Drones are commonly used in numerous applications, such as surveillance, navigation, spraying pesticides in autonomous agricultural systems, various military services, etc., due to their variable sizes and workloads.
Sonain Jamil +2 more
doaj +1 more source
Vision Transformer in Industrial Visual Inspection
Artificial intelligence as an approach to visual inspection in industrial applications has been considered for decades. Recent successes, driven by advances in deep learning, present a potential paradigm shift and have the potential to facilitate an ...
Nils Hütten +2 more
doaj +1 more source
Vision Transformer Adapters for Generalizable Multitask Learning [PDF]
We introduce the first multitasking vision transformer adapters that learn generalizable task affinities which can be applied to novel tasks and domains.
Salzmann, Mathieu +2 more
core +5 more sources
Supervised deep learning with vision transformer predicts delirium using limited lead EEG
As many as 80% of critically ill patients develop delirium increasing the need for institutionalization and higher morbidity and mortality. Clinicians detect less than 40% of delirium when using a validated screening tool.
Malissa A. Mulkey +4 more
doaj +1 more source
Splitting expands the application range of Vision Transformer -- variable Vision Transformer (vViT) [PDF]
Vision Transformer (ViT) has achieved outstanding results in computer vision. Although there are many Transformer-based architectures derived from the original ViT, the dimension of patches are often the same with each other. This disadvantage leads to a
Usuzaki, Takuma
core

