AAT: An Efficient Model for Synthesizing Long Sequences on a Small Dataset

Lecture Notes in Computer Science - Multi-disciplinary Trends in Artificial Intelligence ◽

10.1007/978-3-030-33709-4_7 ◽

2019 ◽

pp. 76-86

Author(s):

Quan Anh Minh Nguyen ◽

Quang Trinh Le ◽

Huu Quoc Van ◽

Duc Dung Nguyen

Keyword(s):

Small Dataset

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Analysis of Using Regularization Technique in The Convolutional Neural Network Architecture to Detect Paddy Disease for Small Dataset

Journal of Physics Conference Series ◽

10.1088/1742-6596/1726/1/012010 ◽

2021 ◽

Vol 1726 ◽

pp. 012010

Author(s):

S Mujahidin ◽

N F Azhar ◽

B Prihasto

Keyword(s):

Neural Network ◽

Convolutional Neural Network ◽

Network Architecture ◽

Neural Network Architecture ◽

Regularization Technique ◽

Small Dataset

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Efficient Transfer Laerning Used in the Classification of Gastroscopic Images with Small Dataset

2020 17th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP) ◽

10.1109/iccwamtip51612.2020.9317450 ◽

2020 ◽

Author(s):

Wenju Du ◽

Rao Nini ◽

Wang Yingchun ◽

Dingcan Hu ◽

Yong Jiahao

Keyword(s):

Small Dataset ◽

Efficient Transfer

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Improving Facial Recognition of FaceNet in a small dataset using DeepFakes

2020 4th International Conference on Computer, Communication and Signal Processing (ICCCSP) ◽

10.1109/icccsp49186.2020.9315253 ◽

2020 ◽

Author(s):

Ansh Abhay Balde ◽

Abhay Jain ◽

Dipti Patra

Keyword(s):

Facial Recognition ◽

Small Dataset

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Adding geodesic information and stochastic patch-wise image prediction for small dataset learning

Neurocomputing ◽

10.1016/j.neucom.2021.01.108 ◽

2021 ◽

Author(s):

Adam Hammoumi ◽

Maxime Moreaud ◽

Christophe Ducottet ◽

Sylvain Desroziers

Keyword(s):

Image Prediction ◽

Small Dataset

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Benchmarking Small-Dataset Structure-Activity-Relationship Models for Prediction of Wnt Signaling Inhibition

IEEE Access ◽

10.1109/access.2020.3046190 ◽

2020 ◽

Vol 8 ◽

pp. 228831-228840

Author(s):

Mahtab Kokabi ◽

Matthew Donnelly ◽

Guangyu Xu

Keyword(s):

Wnt Signaling ◽

Structure Activity Relationship ◽

Activity Relationship ◽

Structure Activity ◽

Small Dataset

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Fully Convolutional Network Variations and Method on Small Dataset

2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE) ◽

10.1109/iccece51280.2021.9342059 ◽

2021 ◽

Author(s):

Tianyou Hu ◽

Yancong Deng ◽

Yuwei Deng ◽

Anmin Ge

Keyword(s):

Convolutional Network ◽

Fully Convolutional Network ◽

Small Dataset

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Detecting Alzheimer's Disease on Small Dataset: A Knowledge Transfer Perspective

IEEE Journal of Biomedical and Health Informatics ◽

10.1109/jbhi.2018.2839771 ◽

2019 ◽

Vol 23 (3) ◽

pp. 1234-1242 ◽

Cited By ~ 7

Author(s):

Wei Li ◽

Yifei Zhao ◽

Xi Chen ◽

Yang Xiao ◽

Yuanyuan Qin

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Knowledge Transfer ◽

Small Dataset

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Voice And Stream: Perceptual And Computational Modeling Of Voice Separation

Music Perception An Interdisciplinary Journal ◽

10.1525/mp.2008.26.1.75 ◽

2008 ◽

Vol 26 (1) ◽

pp. 75-94 ◽

Cited By ~ 19

Author(s):

Emilios Cambouropoulos

Keyword(s):

Computational Modeling ◽

Specific Problem ◽

Cognitive Task ◽

Ground Truth ◽

Musical Score ◽

Auditory Stream ◽

Multiple Voices ◽

Proposed Model ◽

Single Voice ◽

Small Dataset

LISTENERS ARE THOUGHT TO BE CAPABLE of perceiving multiple voices in music. This paper presents different views of what 'voice' means and how the problem of voice separation can be systematically described, with a view to understanding the problem better and developing a systematic description of the cognitive task of segregating voices in music. Well-established perceptual principles of auditory streaming are examined and then tailored to the more specific problem of voice separation in timbrally undifferentiated music. Adopting a perceptual view of musical voice, a computational prototype is developed that splits a musical score (symbolic musical data) into different voices. A single 'voice' may consist of one or more synchronous notes that are perceived as belonging to the same auditory stream. The proposed model is tested against a small dataset that acts as ground truth. The results support the theoretical viewpoint adopted in the paper.

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