Results 71 to 80 of about 24,031,398 (300)
An adaptive fusion-based data augmentation method for abstract dialogue summarization [PDF]
PeerJ Computer ScienceThe dialogue summarization is necessary for information retrieval, and the training of abstract dialogue summarization models heavily rely on large amounts of labeled data.
Weihao Li +4 more
doaj +2 more sources
Data Augmentation using Counterfactuals: Proximity vs Diversity
Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2022 Counterfactual explanations are gaining in popularity as a way of explaining machine learning models. Counterfactual examples are generally created to help interpret the decision of a model.
Md Golam Moula Mehedi Hasan +1 more
doaj +1 more source
Engineering peptides into antibodies—opportunities and strategies for therapeutic innovation
FEBS Letters, EarlyView.Peptides and antibodies occupy complementary therapeutic niches. Peptides recognize difficult targets in a compact format, while antibodies add specificity, long half‐life, and effector functions. This review examines strategies that merge both modalities—peptide grafting into loops, terminal and Fc fusions, and bioconjugation—highlighting how ...
Jinling Wang +2 more
wiley +1 more source
Empirical copula-based data augmentation for mixed-type datasets: a robust approach for synthetic data generation [PDF]
PeerJ Computer ScienceData augmentation is a critical technique for enhancing model performance in scenarios with limited, sparse, or imbalanced datasets. While existing methods often focus on homogeneous data types (e.g., continuous-only or categorical-only), real-world ...
Mohsen Ben Hassine, Lamine Mili
doaj +2 more sources
Implicit Semantic Data Augmentation for Hand Pose Estimation
IEEE Access, 2022 Data augmentation is a well-known technique used for improving the generalization performance of modern neural networks. After the success of several traditional random data augmentation for images (including flipping, translation, or rotation), a recent
Kyeongeun Seo +3 more
doaj +1 more source
Liver organoids: modelling complexity in homeostasis and disease
FEBS Letters, EarlyView.Studying liver in vitro has been challenging because simple 2D cell cultures fail to capture liver's cellular and architectural complexity. To bridge this gap, scientists increasingly use organoids, 3D liver models which better mimic liver composition and function. This review examines recent advances in liver organoid complexity and realism, discusses
Anna M. Dowbaj, Meritxell Huch
wiley +1 more source
Adversarial Action Data Augmentation for Similar Gesture Action Recognition
, 2019 Human gestures are unique for recognizing and describing human actions, and video-based human action recognition techniques are effective solutions to varies real-world applications, such as surveillance, video indexing, and human-computer interaction ...
Michael Blumenstein +11 more
core +1 more source
Handwriting Recognition using Deep Learning with Effective Data Augmentation Techniques [PDF]
, 2021 Machine learning techniques have been successfully used in deciphering handwritten text. Deep learning has made further improvements in this regard. However, they require substantial amounts of training data.
Lidzhade, Ipfi, Brown, Dane L
core
FEBS Letters, EarlyView.This review focuses on the role of autophagy and mitophagy in maintaining pancreatic β‐cell function and homeostasis. We discuss how genetic defects affecting these pathways contribute to the development of type 1, type 2, monogenic, and gestational diabetes. We further explore their potential as therapeutic targets. Created in BioRender.
Yunkyeong Lee +2 more
wiley +1 more source
LLM-Based Persona-Driven Text Data Augmentation
IEEE AccessIllicit online communication, such as drug-dealing dialogues, is increasingly conducted through covert, context dependent language patterns that evade traditional detection techniques in South Korea.
Hyeon Seong Jeong +3 more
doaj +1 more source