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Found 9 papers, 2 papers with code
Rhyme-aware Chinese lyric generator based on GPT
Neural language representation models such as GPT, pre-trained on large-scale corpora, can effectively capture rich semantic patterns from plain text and be fine-tuned to consistently improve natural language generation performance.
DVPE: Divided View Position Embedding for Multi-View 3D Object Detection
Sparse query-based paradigms have achieved significant success in multi-view 3D detection for autonomous vehicles.
Research on the Application of Computer Vision Based on Deep Learning in Autonomous Driving Technology
This research aims to explore the application of deep learning in autonomous driving computer vision technology and its impact on improving system performance.
Mapping New Realities: Ground Truth Image Creation with Pix2Pix Image-to-Image Translation
Generative Adversarial Networks (GANs) have significantly advanced image processing, with Pix2Pix being a notable framework for image-to-image translation.
Large Language Model (LLM) AI text generation detection based on transformer deep learning algorithm
The test set confusion matrix and accuracy show that the model has 99% prediction accuracy for AI-generated text, with a precision of 0. 99, a recall of 1, and an f1 score of 0. 99, achieving a very high classification accuracy.
Advanced Feature Manipulation for Enhanced Change Detection Leveraging Natural Language Models
Change detection is a fundamental task in computer vision that processes a bi-temporal image pair to differentiate between semantically altered and unaltered regions.
Comprehensive evaluation of Mal-API-2019 dataset by machine learning in malware detection
This study conducts a thorough examination of malware detection using machine learning techniques, focusing on the evaluation of various classification models using the Mal-API-2019 dataset.
Open-World Object Detection via Discriminative Class Prototype Learning
Open-world object detection (OWOD) is a challenging problem that combines object detection with incremental learning and open-set learning.
Automated Movement Detection with Dirichlet Process Mixture Models and Electromyography
This study proposes a framework for automated limb-movement detection by fusing data from two EMG sensors (from the left and right limb) through a Dirichlet process mixture model.
