Advanced user credit risk prediction model using lightgbm, xgboost and tabnet with smoteenn
Bank credit risk is a significant challenge in modern financial transactions, and the ability to
identify qualified credit card holders among a large number of applicants is crucial for the …
identify qualified credit card holders among a large number of applicants is crucial for the …
Taskclip: Extend large vision-language model for task oriented object detection
Task-oriented object detection aims to find objects suitable for accomplishing specific tasks.
As a challenging task, it requires simultaneous visual data processing and reasoning under …
As a challenging task, it requires simultaneous visual data processing and reasoning under …
[PDF][PDF] Advancements in AI for Oncology: Developing an Enhanced YOLOv5-based Cancer Cell Detection System
As artificial intelligence (AI) theory becomes more sophisticated and its utilization spreads
across daily life, education, and professional settings, the adoption of AI for medical …
across daily life, education, and professional settings, the adoption of AI for medical …
Application of an ANN and LSTM-based Ensemble Model for Stock Market Prediction
F Liu, S Guo, Q Xing, X Sha, Y Chen… - 2024 IEEE 7th …, 2024 - ieeexplore.ieee.org
Stock trading has always been a key economic indicator in modern society and a primary
source of profit for financial giants such as investment banks, quantitative trading firms, and …
source of profit for financial giants such as investment banks, quantitative trading firms, and …
TinyData: joint dataset condensation with dimensionality reduction
Y Liu, Y Shen - 2024 32nd European Signal Processing …, 2024 - ieeexplore.ieee.org
Training deep neural networks (DNNs) with large-scale datasets poses considerable
challenges due to the computational complexity stemming from the vast number of samples …
challenges due to the computational complexity stemming from the vast number of samples …
Efficient Exploration in Edge-Friendly Hyperdimensional Reinforcement Learning
Integrating deep learning with Reinforcement Learning (RL) results in algorithms that
achieve human-like learning in complex yet unknown environments via a process of trial …
achieve human-like learning in complex yet unknown environments via a process of trial …
EcoSense: Energy-Efficient Intelligent Sensing for In-Shore Ship Detection through Edge-Cloud Collaboration
Detecting marine objects inshore presents challenges owing to algorithmic intricacies and
complexities in system deployment. We propose a difficulty-aware edge-cloud collaborative …
complexities in system deployment. We propose a difficulty-aware edge-cloud collaborative …
Optimized Credit Score Prediction via an Ensemble Model and SMOTEENN Integration
Credit scores are crucial these days for getting approved for a mortgage, assessing
business loans, and managing customer finances. A bank's ability to accurately judge …
business loans, and managing customer finances. A bank's ability to accurately judge …