Results 41 to 50 of about 1,582,815 (295)
V-LTCS: Backbone exploration for Multimodal Misogynous Meme detection
Natural Language Processing JournalMemes have become a fundamental part of online communication and humour, reflecting and shaping the culture of today’s digital age. The amplified Meme culture is inadvertently endorsing and propagating casual Misogyny. This study proposes V-LTCS (Vision-
Sneha Chinivar +3 more
doaj +1 more source
, 2023 The recent developments of deep learning cover a wide variety of tasks such as image classification, text translation, playing go, and folding proteins. All these successful methods depend on a gradient-based learning algorithm to train a model on massive amounts of data using significant computation power.
openaire +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.
Bhattacharjee, Deblina +2 more
core +3 more sources
Privacy-Preserving Semantic Segmentation Using Vision Transformer
Journal of Imaging, 2022 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 transformer (SETR).
Hitoshi Kiya +3 more
doaj +1 more source
Transforming glaucoma diagnosis: transformers at the forefront
Frontiers in Artificial IntelligenceAlthough the Vision Transformer architecture has become widely accepted as the standard for image classification tasks, using it for object detection in computer vision poses significant challenges.
Farheen Chincholi, Harald Koestler
doaj +1 more source
Leveraging Transfer Learning for Accurate CRP Level Prediction in Diabetic Patients
Zanco Journal of Pure and Applied SciencesThis study addresses the challenge of predicting C-reactive protein (CRP) levels in patients with type 2 diabetes mellitus by integrating tabular-to-image transformation techniques with transfer learning architectures.
Alaa J. Albaqal, Mardin A. Anwar
doaj +1 more source
GaitTriViT and GaitVViT: Transformer-based methods emphasizing spatial or temporal aspects in gait recognition [PDF]
PeerJ Computer ScienceIn image recognition tasks, subjects with long distances and low resolution remain a challenge, whereas gait recognition, identifying subjects by walking patterns, is considered one of the most promising biometric technologies due to its stability and ...
Hongyun Sheng
doaj +2 more sources
QuantumIn this work, quantum transformers are designed and analysed in detail by extending the state-of-the-art classical transformer neural network architectures known to be very performant in natural language processing and image analysis. Building upon the previous work, which uses parametrised quantum circuits for data loading and orthogonal neural layers,
El Amine Cherrat +5 more
openaire +4 more sources
MoCoViT: Mobile Convolutional Vision Transformer
, 2022 Recently, Transformer networks have achieved impressive results on a variety of vision tasks. However, most of them are computationally expensive and not suitable for real-world mobile applications.
Ma, Hailong +5 more
core
Ethical Foreground and Background in Adult Educator Work
New Directions for Adult and Continuing Education, EarlyView.ABSTRACT Adult educators work in a complex ethical environment. The very act of contributing to the learning of another is fraught with moral overtones. In this paper we consider the ethical dimensions of adult educator practice by distinguishing the ethical features of the context or ‘background’ of practice from the ethical capabilities and decision ...
Steven Hodge, Sonal Nakar
wiley +1 more source