Results 111 to 120 of about 1,683,190 (291)
Ferroelectric Quantum Dots for Retinomorphic In‐Sensor Computing
This work has provided a protocol for fabricating retinomorphic phototransistors by integrating ferroelectric ligands with quantum dots. The resulting device combines ferroelectricity, optical responsiveness, and low‐power operation to enable adaptive signal amplification and high recognition accuracy under low‐light conditions, while supporting ...
Tingyu Long +26 more
wiley +1 more source
This paper presents a comprehensive comparison between Vision Transformers and Convolutional Neural Networks for face recognition related tasks, including extensive experiments on the tasks of face identification and verification.
Marcos Rodrigo +2 more
doaj +1 more source
Ultrasound Image Analysis with Vision Transformers—Review
Ultrasound (US) has become a widely used imaging modality in clinical practice, characterized by its rapidly evolving technology, advantages, and unique challenges, such as a low imaging quality and high variability.
Majid Vafaeezadeh +2 more
doaj +1 more source
Bioinspired Adaptive Sensors: A Review on Current Developments in Theory and Application
This review comprehensively summarizes the recent progress in the design and fabrication of sensory‐adaptation‐inspired devices and highlights their valuable applications in electronic skin, wearable electronics, and machine vision. The existing challenges and future directions are addressed in aspects such as device performance optimization ...
Guodong Gong +12 more
wiley +1 more source
Vision Transformer With Quadrangle Attention
Window-based attention has become a popular choice in vision transformers due to its superior performance, lower computational complexity, and less memory footprint. However, the design of hand-crafted windows, which is data-agnostic, constrains the flexibility of transformers to adapt to objects of varying sizes, shapes, and orientations.
Qiming Zhang 0001 +3 more
openaire +3 more sources
AI‐Assisted Workflow for (Scanning) Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling. Abstract (Scanning) transmission electron microscopy ((S)TEM) has significantly advanced materials science but faces challenges in correlating precise atomic structure information with the functional properties of ...
Marc Botifoll +19 more
wiley +1 more source
Quantum Machine Learning: Towards Hybrid Quantum-Classical Vision Models
The emergence of deep vision models such as convolutional neural networks and vision transformers has revolutionized computer vision, enabling significant advancements in image classification, object detection, and segmentation.
Syed Muhammad Abuzar Rizvi +4 more
doaj +1 more source
Vision transformer for contrastive clustering
Vision Transformer (ViT) has shown its advantages over the convolutional neural network (CNN) with its ability to capture global long-range dependencies for visual representation learning. Besides ViT, contrastive learning is another popular research topic recently. While previous contrastive learning works are mostly based on CNNs, some recent studies
Hua-Bao Ling +5 more
openaire +2 more sources
Opportunities of Semiconducting Oxide Nanostructures as Advanced Luminescent Materials in Photonics
The review discusses the challenges of wide and ultrawide bandgap semiconducting oxides as a suitable material platform for photonics. They offer great versatility in terms of tuning microstructure, native defects, doping, anisotropy, and micro‐ and nano‐structuring. The review focuses on their light emission, light‐confinement in optical cavities, and
Ana Cremades +7 more
wiley +1 more source
Background/Objectives: This study explores the application of vision transformers to predict early responses to stereotactic radiosurgery in patients with brain metastases using minimally pre-processed magnetic resonance imaging scans.
Simona Ruxandra Volovăț +9 more
doaj +1 more source

