Results 31 to 40 of about 1,373,967 (287)
IEEE Open Journal of Intelligent Transportation Systems, 2023 In this paper, we investigate the use of Vision Transformers for processing and understanding visual data in an autonomous driving setting. Specifically, we explore the use of Vision Transformers for semantic segmentation and monocular depth estimation ...
Durga Prasad Bavirisetti +3 more
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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
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Identifying the role of vision transformer for skin cancer—A scoping review
Frontiers in Artificial Intelligence, 2023 IntroductionDetecting and accurately diagnosing early melanocytic lesions is challenging due to extensive intra- and inter-observer variabilities. Dermoscopy images are widely used to identify and study skin cancer, but the blurred boundaries between ...
Sulaiman Khan, Hazrat Ali, Zubair Shah
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IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023 code: https://github.com/OpenNLPLab/Vicinity-Vision ...
Weixuan Sun +9 more
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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
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Machine Graphics & Vision, 2023 Open, broken, and improperly closed manholes can pose problems for autonomous vehicles and thus need to be included in obstacle avoidance and lane-changing algorithms. In this work, we propose and compare multiple approaches for manhole localization and
Shika Rao, Nitya Mitnala
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Re-Introducing BN Into Transformers for Vision Tasks
IEEE Access, 2023 In recent years, Transformer-based models have exhibited significant advancements over previous models in natural language processing and vision tasks. This powerful methodology has also been extended to the 3D point cloud domain, where it can mitigate ...
Xue-Song Tang, Xian-Lin Xie
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Polyp-PVT: Polyp Segmentation with Pyramid Vision Transformers
CAAI Artificial Intelligence Research, 2023 Most polyp segmentation methods use convolutional neural networks (CNNs) as their backbone, leading to two key issues when exchanging information between the encoder and decoder: (1) taking into account the differences in contribution between different ...
Bo Dong +5 more
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BUViTNet: Breast Ultrasound Detection via Vision Transformers
Diagnostics, 2022 Convolutional neural networks (CNNs) have enhanced ultrasound image-based early breast cancer detection. Vision transformers (ViTs) have recently surpassed CNNs as the most effective method for natural image analysis. ViTs have proven their capability of
Gelan Ayana, Se-woon Choe
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The response of transformers to geomagnetically induced- like currents [PDF]
, 2014 Includes bibliographical references.This dissertation discusses the development and implementation of a rigorously developed protocol for characterizing and testing transformers with GIC-like currents based on their magnetization curve characteristics ...
Chisepo, Hilary K
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