Few-Shot Classification With Intra-Class Unrelated Multi-Prototype Representation and Episode Adaptation Strategy

In this research, there was considered a challenge of constructing a system of scientific knowledge of the shot conditions in judicial ballistics. It was observed that there are underlying factors that are intended to ensureits [scientific knowledge] consistency: identification of the list of shot conditions, which require consideration when solving expert-level research tasks on weapons, cartridges and traces of their action; determination of the communication systems in the course of objects’ interaction, which present the result of exposure to the conditions of the shot; classification of the shot conditions based on the grounds significant for solving scientific and practical problems. The article contains the characteristics of a constructive, functional factor (condition) of weapons and cartridges influence, environmental and fire factors, the structure of the target and its physical properties, situational and spatial factors, and projectile energy characteristics. Highlighted are the forms of connections formed in the course of objects’ interaction, proposed are the author’s classifications of forensically significant shooting conditions with them being divided on the basis of the following criteria: production from the object of interaction, production from a natural phenomenon, production method, results weapon operation and utilization, duration of exposure, type of structural connections between interaction objects, number of conditions that apply when firing and the forming traces.

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KELOMPOK MUSIK REJUNG PESIRAH: STRATEGI ADAPTASI PADA MASYARAKAT PALEMBANG

Tonika: Jurnal Penelitian dan Pengkajian Seni ◽

10.37368/tonika.v2i2.106 ◽

2019 ◽

Vol 2 (2) ◽

pp. 27-37

Author(s):

Dwi Putri Agustini

Keyword(s):

Cultural Anthropology ◽

Case Study Research ◽

Traditional Music ◽

Adaptation Strategy ◽

The People ◽

Musical Arrangements ◽

The Face ◽

Cultural Modification ◽

Traditional Arts

The present phenomenon has clearly brought a change and the influence of the development of traditional music in Palembang society, if this is not carefully addressed, it will experience a shift, alienation and even lose its supporters. The rejung pesirah music group is one of the music groups that still maintains traditional arts in the people of Palembang. This study examines how the adaptation strategy of the rejung pesirah music group in dealing with changes and developments in Palembang society. For this reason, the approach used is cultural anthropology with qualitative case study research methods in Palembang. Data collection is done through observation, interviews and document studies that use triangulation techniques as the validation of the data, while for data analysis through content analysis and interactive models. The results showed that the adaptation strategy undertaken by the rejung pesirah music group was an act and creative ability and had a positive mindset, understanding in responding to changes and needs as an impulse to develop in the face of environmental change and development through learning processes and cultural modification, which resulted a creativity that is the creation of songs, musical arrangements, and musical instruments in the rejung pesirah music group.

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กลยุทธ์ส่วนประสมทางการตลาดเพื่อสร้างความได้เปรียบทางการแข่งขันของธุรกิจร้านค้าปลีกแบบดั้งเดิมในจังหวัดมหาสารคาม (Marketing Adaptation Strategy for Competitive Advantage of Traditional Retailers in Maha Sarakham Province)

SSRN Electronic Journal ◽

10.2139/ssrn.3553093 ◽

2019 ◽

Author(s):

Aranya Udomdat ◽

Kittichai Jaroenchai ◽

Kemika Sansom

Keyword(s):

Competitive Advantage ◽

Adaptation Strategy

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Robust Re-weighting Prototypical Networks for Few-Shot Classification

2020 6th International Conference on Robotics and Artificial Intelligence ◽

10.1145/3449301.3449325 ◽

2020 ◽

Author(s):

Junjie Zhu ◽

Xiaodong Yi ◽

Naiyang Guan ◽

Hang Cheng

Keyword(s):

Shot Classification

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Meta Learning for Few-Shot One-Class Classification

AI ◽

10.3390/ai2020012 ◽

2021 ◽

Vol 2 (2) ◽

pp. 195-208

Author(s):

Gabriel Dahia ◽

Maurício Pamplona Segundo

Keyword(s):

Feature Representation ◽

Support Vector ◽

Support Vector Data Description ◽

Target Class ◽

Feature Representations ◽

Shot Classification ◽

Training Stage ◽

Comparable Performance ◽

Meta Learning ◽

One Class Classification

We propose a method that can perform one-class classification given only a small number of examples from the target class and none from the others. We formulate the learning of meaningful features for one-class classification as a meta-learning problem in which the meta-training stage repeatedly simulates one-class classification, using the classification loss of the chosen algorithm to learn a feature representation. To learn these representations, we require only multiclass data from similar tasks. We show how the Support Vector Data Description method can be used with our method, and also propose a simpler variant based on Prototypical Networks that obtains comparable performance, indicating that learning feature representations directly from data may be more important than which one-class algorithm we choose. We validate our approach by adapting few-shot classification datasets to the few-shot one-class classification scenario, obtaining similar results to the state-of-the-art of traditional one-class classification, and that improves upon that of one-class classification baselines employed in the few-shot setting.

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