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Objective Video Quality Assessment Method for Object Recognition Tasks
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Objective Video Quality Assessment Method for Object Recognition Tasks

Leszczuk, Mikołaj ; Janowski, Lucjan ; Nawała, Jakub ; Boev, Atanas

Electronics (Basel), 2024-05, Vol.13 (9), p.1750 [Periódico revisado por pares]

Basel: MDPI AG

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12
Fast machine learning annotation in the medical domain: a semi-automated video annotation tool for gastroenterologists
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Fast machine learning annotation in the medical domain: a semi-automated video annotation tool for gastroenterologists

Krenzer, Adrian ; Makowski, Kevin ; Hekalo, Amar ; Fitting, Daniel ; Troya, Joel ; Zoller, Wolfram G ; Hann, Alexander ; Puppe, Frank

Biomedical engineering online, 2022-05, Vol.21 (1), p.33-33, Article 33 [Periódico revisado por pares]

England: BioMed Central Ltd

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13
Classification of Tennis Video Types Based on Machine Learning Technology
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Classification of Tennis Video Types Based on Machine Learning Technology

Gong, Xun ; Wang, Fucheng Wu, Wenqing ; Wenqing Wu

Wireless communications and mobile computing, 2021-06, Vol.2021, p.1-11 [Periódico revisado por pares]

Oxford: Hindawi

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14
DeMAAE: deep multiplicative attention-based autoencoder for identification of peculiarities in video sequences
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DeMAAE: deep multiplicative attention-based autoencoder for identification of peculiarities in video sequences

Aslam, Nazia ; Kolekar, Maheshkumar H.

The Visual computer, 2024-03, Vol.40 (3), p.1729-1743 [Periódico revisado por pares]

Berlin/Heidelberg: Springer Berlin Heidelberg

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15
From Video to Hyperspectral: Hyperspectral Image-Level Feature Extraction with Transfer Learning
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From Video to Hyperspectral: Hyperspectral Image-Level Feature Extraction with Transfer Learning

Sun, Yifan ; Liu, Bing ; Yu, Xuchu ; Yu, Anzhu ; Gao, Kuiliang ; Ding, Lei

Remote sensing (Basel, Switzerland), 2022-10, Vol.14 (20), p.5118 [Periódico revisado por pares]

Basel: MDPI AG

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16
ACCV: automatic classification algorithm of cataract video based on deep learning
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ACCV: automatic classification algorithm of cataract video based on deep learning

Hu, Shenming ; Luan, Xinze ; Wu, Hong ; Wang, Xiaoting ; Yan, Chunhong ; Wang, Jingying ; Liu, Guantong ; He, Wei

Biomedical engineering online, 2021-08, Vol.20 (1), p.78-78, Article 78 [Periódico revisado por pares]

England: BioMed Central Ltd

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17
Deep Learning for Activity Recognition Using Audio and Video
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Deep Learning for Activity Recognition Using Audio and Video

Reinolds, Francisco ; Neto, Cristiana ; Machado, José

Electronics (Basel), 2022-03, Vol.11 (5), p.782 [Periódico revisado por pares]

Basel: MDPI AG

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18
Spatial–Spectral Cross-Correlation Embedded Dual-Transfer Network for Object Tracking Using Hyperspectral Videos
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Spatial–Spectral Cross-Correlation Embedded Dual-Transfer Network for Object Tracking Using Hyperspectral Videos

Lei, Jie ; Liu, Pan ; Xie, Weiying ; Gao, Long ; Li, Yunsong ; Du, Qian

Remote sensing (Basel, Switzerland), 2022-08, Vol.14 (15), p.3512 [Periódico revisado por pares]

Basel: MDPI AG

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19
Video Object Segmentation Using Multi-Scale Attention-Based Siamese Network
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Video Object Segmentation Using Multi-Scale Attention-Based Siamese Network

Zhu, Zhiliang ; Qiu, Leiningxin ; Wang, Jiaxin ; Xiong, Jinquan ; Peng, Hua

Electronics (Basel), 2023-07, Vol.12 (13), p.2890 [Periódico revisado por pares]

Basel: MDPI AG

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20
Enhancing DeepFake Detection: Leveraging Mesonet for Video Fraud Identification
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Enhancing DeepFake Detection: Leveraging Mesonet for Video Fraud Identification

Shanmuganathan, C. ; Thamizharasi, M. ; Anish, T. P. ; Sivasankari, K.

SN computer science, 2024-03, Vol.5 (3), p.301, Article 301 [Periódico revisado por pares]

Singapore: Springer Nature Singapore

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