Comparative analysis of transformer architectures for brain tumor classification [PDF]
Exploration of MedicineAim: Early and accurate diagnosis of brain tumors is critical for treatment success, but manual magnetic resonance imaging (MRI) interpretation has limitations.
Yigitcan Cakmak, Ishak Pacal
doaj +1 more source
Enhancing medical image segmentation with a multi-transformer U-Net [PDF]
PeerJVarious segmentation networks based on Swin Transformer have shown promise in medical segmentation tasks. Nonetheless, challenges such as lower accuracy and slower training convergence have persisted. To tackle these issues, we introduce a novel approach
Yongping Dan +3 more
doaj +2 more sources
Estimating glue-layer defects on plywood through computer vision methods [PDF]
, 2023 Making quality film-faced plywood is a vital issue for the manufacturer as it decides the quality of the end product made from this film-faced plywood.
Baad, Swapnil
core
Design of Single-Switch Inverters for Variable Resistance/Load Modulation Operation [PDF]
, 2014 Single-Switch inverters such as the conventional Class-E inverter are often highly load sensitive, and maintain zero-voltage switching over only a narrow range of load resistances.
Al Bastami, Anas Ibrahim +3 more
core +1 more source
Vision transformer and explainable transfer learning models for auto detection of kidney cyst, stone and tumor from CT-radiography [PDF]
, 2022 Renal failure, a public health concern, and the scarcity of nephrologists around the globe have necessitated the development of an AI-based system to auto-diagnose kidney diseases.
Alam, Md Golam Rabiul +5 more
core +2 more sources
Center Point Target Detection Algorithm Based on Improved Swin Transformer [PDF]
Jisuanji kexueAiming at the shortcomings of Swin Transformer in extracting local feature information and expressing features,this paper proposes a center point target detection algorithm based on improved Swin Transformer to improve its performance in target detection.
LIU Jiasen, HUANG Jun
doaj +1 more source
SSformer: A Lightweight Transformer for Semantic Segmentation
, 2022 It is well believed that Transformer performs better in semantic segmentation compared to convolutional neural networks. Nevertheless, the original Vision Transformer may lack of inductive biases of local neighborhoods and possess a high time complexity.
Gao, Pan, Shi, Wentao, Xu, Jing
core
gSwin: Gated MLP Vision Model with Hierarchical Structure of Shifted Window
, 2023 Following the success in language domain, the self-attention mechanism (transformer) is adopted in the vision domain and achieving great success recently. Additionally, as another stream, multi-layer perceptron (MLP) is also explored in the vision domain.
Go, Mocho, Tachibana, Hideyuki
core +1 more source
A wheat spike detection method based on Transformer
Frontiers in Plant Science, 2022 Wheat spike detection has important research significance for production estimation and crop field management. With the development of deep learning-based algorithms, researchers tend to solve the detection task by convolutional neural networks (CNNs ...
Qiong Zhou +11 more
doaj +1 more source
Swin on Axes:Extending Swin Transformers to Quadtree Image Representations [PDF]
2024 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW)In recent years, Transformer models have revolutionized machine learning. While this has resulted in impressive re-sults in the field of Natural Language Processing, Computer Vision quickly stumbled upon computation and memory problems due to the high resolution and dimensionality of the input data. This is particularly true for video, where the number
Oliu, Marc +3 more
openaire +2 more sources