Results 21 to 30 of about 1,457,631 (249)
Sensors, 2023 Understanding actions in videos remains a significant challenge in computer vision, which has been the subject of several pieces of research in the last decades.
Oumaima Moutik +6 more
doaj +1 more source
International Journal of Computer Vision, 2023 We attempt to reduce the computational costs in vision transformers (ViTs), which increase quadratically in the token number. We present a novel training paradigm that trains only one ViT model at a time, but is capable of providing improved image recognition performance with various computational costs. Here, the trained ViT model, termed super vision
Mingbao Lin +6 more
openaire +3 more sources
Pre-breakdown Characteristics of Contaminated Power Transformer Oil [PDF]
, 2007 In this paper we have studied pre-breakdown characteristics of transformer oil in the presence of different levels of contamination. The contaminant is fibrous dust from pressboard insulation used for high voltage transformers.
Zuber, H M, Chen, G
core +2 more sources
Transformer-based ripeness segmentation for tomatoes
Smart Agricultural Technology, 2023 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
Transformer architectures for computer vision: A comprehensive review and future research directions [PDF]
EPJ Web of ConferencesLong-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
Vision Transformers Are Robust Learners
Proceedings of the AAAI Conference on Artificial Intelligence, 2022 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
eolphd/transformer-forecasting: transformer-forecasting
, 2023 <p>Main code and modules of a transformer neural network for environmental time series forecasting, including input data used for test. Orozco-López and Kaplan "Interpretable Transformer Neural Network Prediction of Diverse Environmental Time ...
eolphd
core +1 more source
Art authentication with vision transformers
Neural Computing and Applications, 2023 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
AI, 2022 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
, 2008 The paper develops an efficient computational method for establishing equivalent characteristics of magnetic joints of transformer cores, with special emphasis on step-lap design.
N. Nihat +7 more
core +2 more sources