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TransformCode: a contrastive learning framework for code embedding via subtree transformation
Artificial intelligence (AI) has revolutionized software engineering (SE) by enhancing
software development efficiency. The advent of pre-trained models (PTMs) leveraging …
software development efficiency. The advent of pre-trained models (PTMs) leveraging …
zsllmcode: An effective approach for functional code embedding via llm with zero-shot learning
Regarding software engineering (SE) tasks, Large language models (LLMs) have the
capability of zero-shot learning, which does not require training or fine-tuning, unlike pre …
capability of zero-shot learning, which does not require training or fine-tuning, unlike pre …
Convolutional Neural Network Image Classification Based on Different Color Spaces
Although Convolutional Neural Networks (CNNs) have achieved remarkable success in
image classification, most CNNs use image datasets in the Red-Green-Blue (RGB) color …
image classification, most CNNs use image datasets in the Red-Green-Blue (RGB) color …
Hidden Markov models with multivariate bounded asymmetric student's t-mixture model emissions
Abstract Hidden Markov models (HMMs) are popular methods for continuous sequential
data modeling and classification tasks. In such applications, the observation emission …
data modeling and classification tasks. In such applications, the observation emission …
Challenges and Future Developments in the Metaverse
S Wang, W Huang - 2024 2nd International Conference on …, 2024 - ieeexplore.ieee.org
This paper gives a comprehensive overview of the metaverse, focusing on its key
technologies, current challenges and future prospects. Key technologies discussed include …
technologies, current challenges and future prospects. Key technologies discussed include …
Mixture-Based Clustering and Hidden Markov Models for Energy Management and Human Activity Recognition: Novel Approaches and Explainable Applications
HGA Al-Bazzaz - 2023 - spectrum.library.concordia.ca
In recent times, the rapid growth of data in various fields of life has created an immense
need for powerful tools to extract useful information from data. This has motivated …
need for powerful tools to extract useful information from data. This has motivated …
Generative Models Based on the Bounded Asymmetric Student's t-Distribution
O Bouarada - 2023 - spectrum.library.concordia.ca
Gaussian mixture models (GMMs) are a very useful and widely popular approach for
clustering, but they have several limitations, such as low outliers tolerance and assumption …
clustering, but they have several limitations, such as low outliers tolerance and assumption …
The Impact of Color Spaces on Convolutional Neural Network Classification Performance
Image classification has become widely used in computer vision applications in recent
years, including in intrusion detection in video surveillance. While Convolutional Neural …
years, including in intrusion detection in video surveillance. While Convolutional Neural …
Generative Models Based on the Bounded Asymmetric Gaussian Distribution
Z **an - 2021 - spectrum.library.concordia.ca
The bounded asymmetric Gaussian mixture model (BAGMM) has proved that it generally
performs better than the classical Gaussian mixture model. In this thesis, we investigate the …
performs better than the classical Gaussian mixture model. In this thesis, we investigate the …