Results 31 to 40 of about 8,510,788 (298)
Unsupervised Controllable Generation with Self-Training [PDF]
2021 International Joint Conference on Neural Networks (IJCNN), 2021 Recent generative adversarial networks (GANs) are able to generate impressive photo-realistic images. However, controllable generation with GANs remains a challenging research problem. Achieving controllable generation requires semantically interpretable and disentangled factors of variation.
Chrysos, Grigorios G. +3 more
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The effect of assertiveness training on self-efficacy among Iranian high school female students [PDF]
, 2014 The current study considers the effect of assertiveness on the first-grade high school female students’ self-efficacy. The research method is quasi-experimental and the design is pretest posttest with control group.
Nikoogoftar, Mansooreh +1 more
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On the Effectiveness of Self-Training in MOOC Dropout Prediction
Open Computer Science, 2020 Massive open online courses (MOOCs) have gained enormous popularity in recent years and have attracted learners worldwide. However, MOOCs face a crucial challenge in the high dropout rate, which varies between 91%-93%.
Goel Yamini, Goyal Rinkaj
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IEEE Access, 2020 Deep cerebellar nuclei are a key structure of the cerebellum that are involved in processing motor and sensory information. It is thus a crucial step to accurately segment deep cerebellar nuclei for the understanding of the cerebellum system and its ...
Jinyoung Kim +4 more
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Information, 2022 In the age of the digital revolution and the widespread usage of social networks, the modalities of information consumption and production were disrupted by the shift to instantaneous transmission.
Oumaima Stitini +2 more
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Self-trained Panoptic Segmentation
CoRR, 2023 Panoptic segmentation is an important computer vision task which combines semantic and instance segmentation. It plays a crucial role in domains of medical image analysis, self-driving vehicles, and robotics by providing a comprehensive understanding of visual environments.
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, 2012 In some real-world applications, it is time-consuming or expensive to collect much labeled data, while unlabeled data is easier to obtain. Many semi-supervised learning methods have been proposed to deal with this problem by utilizing the unlabeled data. On the other hand, on some datasets, misclassifying different classes causes different costs, which
Guo, Yuanyuan +2 more
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Self Training Autonomous Driving Agent [PDF]
2019 58th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE), 2019 Intrinsically, driving is a Markov Decision Process which suits well the reinforcement learning paradigm. In this paper, we propose a novel agent which learns to drive a vehicle without any human assistance. We use the concept of reinforcement learning and evolutionary strategies to train our agent in a 2D simulation environment.
Shashank Kotyan +2 more
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Self-Training with Entropy-Based Mixup for Low-Resource Chest X-ray Classification
Applied Sciences, 2023 Deep learning-based medical image analysis technology has been developed to the extent that it shows an accuracy surpassing the ability of a human radiologist in some tasks. However, data labeling on medical images requires human experts and a great deal
Minkyu Park, Juntae Kim
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H-ermes: Journal of Communication, 2017 Overlapping between Science of Education and tightrope walking. Our research aims to investigate the possibility of contaminating education and tightrope walking.
Francesca Antonacci, Giulia Schiavone
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