SPJIMR-ReviewPaper-V2 / sample_data.csv
rahull30's picture
Clean commit: preprocessing, clustering, embedding fixes
a0c55ac
Title,Abstract,DOI
Transformer Models for Text Classification,This study explores transformer-based architectures for large-scale text classification tasks. We evaluate models such as BERT and RoBERTa on multiple benchmark datasets and analyze their performance in handling contextual dependencies and long-range semantics in textual data.,10.2000/sample.001
Neural Machine Translation using Attention,We investigate neural machine translation systems that leverage attention mechanisms to improve translation accuracy across multiple languages. The approach demonstrates improved fluency and contextual alignment compared to traditional statistical methods.,10.2000/sample.002
Sentiment Analysis with Deep Learning,This paper presents deep learning techniques for sentiment analysis in social media data. We use recurrent and transformer-based models to capture contextual meaning and achieve improved classification performance across diverse datasets.,10.2000/sample.003
Named Entity Recognition with Transformers,We apply transformer-based models to named entity recognition tasks. The approach leverages contextual embeddings to identify entities such as names locations and organizations with high precision and recall.,10.2000/sample.004
Text Summarization using Seq2Seq Models,We develop sequence-to-sequence models for automatic text summarization. The model generates concise summaries while retaining key information from long documents.,10.2000/sample.005
Language Modeling using GPT Architectures,This study evaluates autoregressive language models for natural language generation tasks. The models demonstrate strong performance in generating coherent and contextually relevant text.,10.2000/sample.006
Question Answering Systems using NLP,We design question answering systems using deep learning models capable of understanding and retrieving relevant information from large text corpora.,10.2000/sample.007
Topic Modeling using Neural Approaches,We propose neural topic modeling methods that improve topic coherence and interpretability compared to traditional probabilistic models.,10.2000/sample.008
Dialogue Systems with Context Awareness,We develop conversational agents capable of maintaining context across multiple turns improving user interaction quality.,10.2000/sample.009
Fake News Detection using NLP Models,This work focuses on detecting misinformation using deep learning and semantic analysis techniques applied to online text data.,10.2000/sample.010
Image Classification using CNN Architectures,We evaluate convolutional neural networks for large-scale image classification tasks. The models achieve high accuracy on benchmark datasets and demonstrate robustness to variations in input data.,10.2000/sample.011
Object Detection with YOLO Models,This paper presents real-time object detection using YOLO architectures capable of detecting multiple objects efficiently in images and video streams.,10.2000/sample.012
Image Segmentation using U-Net,We apply U-Net architecture for precise segmentation of biomedical images enabling accurate identification of regions of interest.,10.2000/sample.013
Face Recognition using Deep Learning,We develop deep learning-based systems for face recognition achieving high accuracy across large datasets with varying lighting and pose conditions.,10.2000/sample.014
Image Captioning with Vision-Language Models,We combine convolutional networks and sequence models to generate descriptive captions for images linking visual understanding with language generation.,10.2000/sample.015
Video Classification using Deep Networks,We analyze video data using deep neural networks capturing both spatial and temporal features for classification tasks.,10.2000/sample.016
Human Pose Estimation using CNN Models,We develop models capable of estimating human body keypoints from images enabling applications in motion analysis and activity recognition.,10.2000/sample.017
Super Resolution using GANs,We use generative adversarial networks to enhance image resolution and improve visual quality.,10.2000/sample.018
Medical Image Analysis with Deep Learning,We apply deep learning techniques to analyze medical images improving diagnostic accuracy and efficiency.,10.2000/sample.019
Autonomous Driving Vision Systems,We design computer vision systems for autonomous vehicles capable of detecting objects lanes and obstacles in real time.,10.2000/sample.020
Reinforcement Learning for Game Playing,We train reinforcement learning agents capable of playing complex games by learning optimal strategies through interaction with the environment.,10.2000/sample.021
Robotic Manipulation using RL,We apply reinforcement learning to robotic systems enabling them to perform manipulation tasks with adaptability.,10.2000/sample.022
Autonomous Navigation using Reinforcement Learning,We develop RL-based navigation systems for autonomous robots operating in dynamic environments.,10.2000/sample.023
Traffic Signal Optimization with RL,We optimize urban traffic signals using reinforcement learning to reduce congestion and improve flow.,10.2000/sample.024
Policy Gradient Methods in RL,We study policy gradient algorithms for solving continuous control problems in reinforcement learning.,10.2000/sample.025
Deep Q Networks for Control Tasks,We apply deep Q-learning methods to solve control tasks demonstrating improved decision-making capabilities.,10.2000/sample.026
Multi-Agent Reinforcement Learning Systems,We explore multi-agent systems where multiple agents learn to cooperate or compete in shared environments.,10.2000/sample.027
Dialogue Optimization using RL,We use reinforcement learning to improve conversational agents based on user feedback.,10.2000/sample.028
Resource Allocation using RL,We apply RL techniques to optimize resource allocation in distributed systems.,10.2000/sample.029
Energy Optimization with RL Models,We develop reinforcement learning approaches for efficient energy consumption management.,10.2000/sample.030
Graph Neural Networks for Social Analysis,We use graph neural networks to analyze social networks identifying communities and relationships.,10.2000/sample.031
Traffic Prediction using Graph Models,We model traffic systems as graphs and apply neural networks to predict congestion patterns.,10.2000/sample.032
Recommendation Systems with Graph Embeddings,We enhance recommendation systems using graph-based representations of user-item interactions.,10.2000/sample.033
Knowledge Graph Completion,We apply machine learning techniques to infer missing relationships in knowledge graphs.,10.2000/sample.034
Fraud Detection using Graph Analysis,We detect fraudulent patterns in financial networks using graph-based learning methods.,10.2000/sample.035
Graph Clustering Techniques,We explore clustering techniques for graph-structured data to identify meaningful communities.,10.2000/sample.036
Graph Attention Networks,We implement attention mechanisms within graph neural networks to improve representation learning.,10.2000/sample.037
Molecular Graph Learning for Chemistry,We apply graph learning techniques to molecular structures for predicting chemical properties.,10.2000/sample.038
Graph-Based Anomaly Detection,We detect anomalies in network structures using graph neural network models.,10.2000/sample.039
Graph Representation Learning,We develop methods for learning embeddings from graph data for downstream machine learning tasks.,10.2000/sample.040
Medical Diagnosis using AI,We develop machine learning models for diagnosing diseases based on clinical and imaging data improving accuracy.,10.2000/sample.041
Brain Tumor Detection using MRI,We use deep learning to identify tumors from MRI scans aiding early diagnosis.,10.2000/sample.042
Drug Discovery using Machine Learning,We apply ML techniques to identify potential drug candidates and accelerate pharmaceutical research.,10.2000/sample.043
Predictive Healthcare Analytics,We analyze patient data to predict disease risk and optimize treatment strategies.,10.2000/sample.044
Genomic Analysis using AI,We apply deep learning to genomic data for identifying genetic patterns and mutations.,10.2000/sample.045
Medical Image Classification,We classify medical images using deep learning for improved diagnosis.,10.2000/sample.046
Disease Prediction using ML Models,We predict diseases using machine learning based on patient history and clinical features.,10.2000/sample.047
Healthcare Recommendation Systems,We develop recommendation systems for personalized healthcare treatment plans.,10.2000/sample.048
AI in Radiology,We use AI techniques to assist radiologists in interpreting medical images.,10.2000/sample.049
Clinical Decision Support Systems,We design systems that assist doctors in making informed decisions using machine learning.,10.2000/sample.050
Fraud Detection using Machine Learning,We detect fraudulent transactions using supervised and unsupervised learning techniques.,10.2000/sample.051
Recommendation Systems for E-Commerce,We develop recommendation engines to improve personalization in online shopping.,10.2000/sample.052
Time Series Forecasting using LSTM,We apply LSTM networks for forecasting financial and environmental time series data.,10.2000/sample.053
Anomaly Detection in Industrial Systems,We detect anomalies in industrial sensor data using machine learning.,10.2000/sample.054
Energy Consumption Prediction,We use machine learning models to predict energy usage patterns in smart grids.,10.2000/sample.055
Cybersecurity Threat Detection,We detect network intrusions and cyber threats using machine learning techniques.,10.2000/sample.056
Smart City Applications using AI,We apply AI techniques for urban planning traffic management and resource optimization.,10.2000/sample.057
AI for Financial Forecasting,We develop models for predicting financial market trends using machine learning.,10.2000/sample.058
Customer Behavior Analysis using ML,We analyze customer data to identify patterns and improve marketing strategies.,10.2000/sample.059
AI for Supply Chain Optimization,We optimize supply chain operations using machine learning models.,10.2000/sample.060