Results 51 to 60 of about 26,776 (176)

Multimodal One-Shot Learning of Speech and Images

open access: yes, 2019
Imagine a robot is shown new concepts visually together with spoken tags, e.g. "milk", "eggs", "butter". After seeing one paired audio-visual example per class, it is shown a new set of unseen instances of these objects, and asked to pick the "milk ...
Eloff, Ryan   +2 more
core   +1 more source

Siamese Cascaded Region Proposal Networks With Channel-Interconnection-Spatial Attention for Visual Tracking

open access: yesIEEE Access, 2020
Trackers based on Siamese networks show great potential in tracking accuracy and speed. However, it is still challenging to adapt offline training model to online tracking. In this paper, a Siamese based tracker (SCRPN-CISA) is proposed, which integrates
Zhoujuan Cui   +3 more
doaj   +1 more source

Ego-Downward and Ambient Video based Person Location Association

open access: yes, 2018
Using an ego-centric camera to do localization and tracking is highly needed for urban navigation and indoor assistive system when GPS is not available or not accurate enough.
Huo, Zhouyuan   +3 more
core   +1 more source

Research on Siamese Object Tracking Algorithm Based on Knowledge Distillation in Marine Environment

open access: yesIEEE Access, 2023
Siamese networks have gained considerable attention for object tracking due to their balance of speed and accuracy. However, existing Siamese tracking algorithms have been too rigid in their predictions of bounding box tags and lack uncertainty ...
Yihong Zhang   +3 more
doaj   +1 more source

A Feature Learning Siamese Model for Intelligent Control of the Dynamic Range Compressor

open access: yes, 2019
In this paper, a siamese DNN model is proposed to learn the characteristics of the audio dynamic range compressor (DRC). This facilitates an intelligent control system that uses audio examples to configure the DRC, a widely used non-linear audio signal ...
Fazekas, György, Sheng, Di
core   +1 more source

Posterior Cortical Atrophy in the Asia‐Pacific: A Report From the PCA Asian Workgroup

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Posterior Cortical Atrophy (PCA) is a distinct dementia syndrome primarily affecting spatial abilities and visual processing. It is associated with degeneration in the posterior part of the brain. PCA is subclassified into PCA‐pure and PCA‐plus syndromes based on consensus criteria.
Yuttachai Likitjaroen   +11 more
wiley   +1 more source

Efficient Visual Tracking With Stacked Channel-Spatial Attention Learning

open access: yesIEEE Access, 2020
Template based learning, particularly Siamese networks, has recently become popular due to balancing accuracy and speed. However, preserving tracker robustness against challenging scenarios with real-time speed is a primary concern for visual object ...
Md. Maklachur Rahman   +2 more
doaj   +1 more source

Composites of Shellac and Silver Nanowires as Flexible, Biobased, and Corrosion‐Resistant Transparent Conductive Electrodes

open access: yesAdvanced Functional Materials, EarlyView.
Shellac, a centuries‐old natural resin, is reimagined as a green material for flexible electronics. When combined with silver nanowires, shellac films deliver transparency, conductivity, and stability against humidity. These results position shellac as a sustainable alternative to synthetic polymers for transparent conductors in next‐generation ...
Rahaf Nafez Hussein   +4 more
wiley   +1 more source

Wide-Area Search Tracking for Siamese Region Proposal Network

open access: yesIEEE Access, 2020
With the introduction of deep learning technology into the field of visual tracking, the accuracy and robustness of visual tracking have greatly improved.
Hongwei Zhang   +3 more
doaj   +1 more source

PVSNet: Palm Vein Authentication Siamese Network Trained using Triplet Loss and Adaptive Hard Mining by Learning Enforced Domain Specific Features

open access: yes, 2018
Designing an end-to-end deep learning network to match the biometric features with limited training samples is an extremely challenging task. To address this problem, we propose a new way to design an end-to-end deep CNN framework i.e., PVSNet that works
Jaswal, Gaurav   +3 more
core   +1 more source

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