AI models are starting to crack high-level math problems

“I was curious to establish a baseline for when LLMs are effectively able to solve open math problems compared to where they ...
Scientific Research Publishing

Spatiotemporal Evolution Patterns and Intelligent Forecasting of Passenger Flow in Megacity High-Speed Rail Hubs: A Case Study of Guangzhou South Railway Station ()

Spatiotemporal Evolution Patterns and Intelligent Forecasting of Passenger Flow in Megacity High-Speed Rail Hubs: A Case ...
IEEE

An Ensemble Deep Learning Model Using CNN, LSTM and Autoencoder for EEG-Based Parkinson’s Disease Classification

Abstract: Parkinson's disease is a neurological disorder hat effects the movements including shaking, stiffness, difficulty while walking and speaking. This condition will occur when the nerve cells ...
IEEE

A CNN and Deep Learning-based Smart Satellite Surveillance System for Wildfire Detection and Wildlife Damage Assessment

Abstract: Wildfires are a growing concern due to their catastrophic impacts on the environment, ecosystem services, biodiversity, and human settlements. Different fire detection systems face ...
IEEE

Development of Scalable Deep Learning Frameworks Utilizing Advanced Hybrid Models like Transformer-CNN for Distributed Computing Environments

Abstract: Over the past few years especially in the context of communication and information processing the importance of Natural language processing which demands efficient deep learning models has ...
IEEE

Multi-Model Deep Learning Architecture for Cryptocurrency Forecasting: A Comparative Evaluation of CNN-LSTM, CNN-Bidirectional LSTM, and CNN-GRU

Abstract: Bitcoin price prediction is a significant challenge. This is due to the fact that Bitcoin prices can fluctuate very quickly and have a lot of potential to make money. There are three hybrid ...
IEEE

Deep Learning Models for Precision Agriculture: Evaluating CNN Architectures for Accurate Plant Disease Detection

Abstract: Early and precise detection of plant diseases is crucial for enhancing crop yield and minimizing agricultural losses. This paper evaluates the performance of deep learning-based ...
IEEE

Deep Learning based Facial Emotion Detection with CNN and FER Models

Abstract: The deep learning framework for facial emotion recognition (FER) using a convolutional neural network (CNN) architecture is described in this research. The model uses data augmentation and ...
GitHub

A Scalable Deep Learning Framework for Wave-Based Inverse Problems

WaveDL is a deep learning framework built for wave-based inverse problems — from ultrasonic NDE and geophysics to biomedical tissue characterization. It provides a robust, scalable training pipeline ...
IEEE

CNN-Based Deep Learning Framework for Multi-Class Rice Leaf Disease Detection and Classification

Abstract: Being a major contributor to rice production worldwide, rice leaf diseases need to be detected early and correctly to achieve maximum output and reduce losses. Processes based on deep ...