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J. Jang

17 papers hereh-index 3323.2k citations208 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author7
  • last author10

Across the 17 of 17 papers where every author was matched, so the position is known.

fields
  • cs.SD12
  • cs.CV2
  • cs.AI1
  • cs.CL1
  • cs.LG1
same name
  • J. Jang — 57 papers, h 41
  • J. Jang — 48 papers, h 20
  • J. Jang — 47 papers, h 29
  • J. Jang — 12 papers, h 11
  • J. Jang — 10 papers, h 1
  • J. Jang — 6 papers, h 8

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20132025
most citedA Hierarchical Approach to Designing Approximate Reasoning-Based Controllers for Dynamic Physical Systems

59 citations · 89 across the 17 of their papers we have counts for

collaborators
Showing 2018Show all

3 papers · 1 filter

cs.SD2018★ 3 cited

Learning to match transient sound events using attentional similarity for few-shot sound recognition

Szu-Yu Chou, Kai-Hsiang Cheng, Jyh-Shing Roger Jang +1

In this paper, we introduce a novel attentional similarity module for the problem of few-shot sound recognition. Given a few examples of an unseen sound event, a classifier must be…

cs.SD2018★ 14 cited

Singing Style Transfer Using Cycle-Consistent Boundary Equilibrium Generative Adversarial Networks

Cheng-Wei Wu, Jen-Yu Liu, Yi-Hsuan Yang +1

Can we make a famous rap singer like Eminem sing whatever our favorite song? Singing style transfer attempts to make this possible, by replacing the vocal of a song from the source…

cs.LG2018

Backpropagation with N-D Vector-Valued Neurons Using Arbitrary Bilinear Products

Zhe-Cheng Fan, Tak-Shing T. Chan, Yi-Hsuan Yang +1

Vector-valued neural learning has emerged as a promising direction in deep learning recently. Traditionally, training data for neural networks (NNs) are formulated as a vector of s…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.