Category: Research
Researchers from U Texas and Apple Propose a Novel Transformer-Based Architecture for Global Multi-Object Tracking
Multi-object tracking aims to locate and track all objects in a video feed. It’s a fundamental component in domains like…
A Comprehensive Introduction to Bayesian Deep Learning
Bayesian (deep) learning has always intrigued and intimidated me. Perhaps because it leans heavily on probabilistic theory, which can be…
Ambitions to become GitHub for machine learning? Hugging Face adds Decision Transformer to its library
Hugging Face is one of the most promising companies in the world. It has set to achieve a unique feat…
Traffic prediction with advanced Graph Neural Networks
By partnering with Google, DeepMind is able to bring the benefits of AI to billions of people all over the…
A beginner’s guide to Bayesian CNN
Applying bayesian on neural networks is a method of controlling overfitting. We can also apply bayesian on CNN to reduce…
Development of a Smart Home Context-aware Application: A Machine Learning based Approach
Context-awareness is an important characteristic of smart home. Several methods are used in context-aware application to provide services. The main…
Context-Aware Computing for IoT: History, Applications and Research Challenges
The new Internet of Things (IoT) technology has the potential to generate breakthrough opportunities in real-life applications. The merger of…
Researchers Build AI That Builds AI
By using hypernetworks, researchers can now preemptively fine-tune artificial neural networks, saving some of the time and expense of training….
Contextual data classification for a ubiquitous intelligent environment
Recognition of activities from sensors is a key paradigm of ubiquitous computing. Activity recognition systems can be used to label…
ANALYZING CONTEXTUAL DATA IN EDUCATIONAL CONTEXT: EDUCATIONAL DATA MINING AND LOGFILE ANALYSIS
In recent decades,attention has been focused on analyzing contextual data in educational contextusingeducational data mining (EDM), which is a process…
Stock Price Forecasting by a Deep Convolutional Generative Adversarial Network
Stock market prices are known to be very volatile and noisy, and their accurate forecasting is a challenging problem. Traditionally,…
Stock Prediction Using Convolutional Neural Network
Stock prediction is a very hot topic in our life. However, in the early time, because ofsome reasons and the…
A Survey on Machine Learning for Stock Price Prediction: Algorithms and Techniques
Stock market trading is an activity in which investors need fast and accurate information to make effectivedecisions. Since many stocks…
Academia : Research Papers on Convolution Neural Networks
REVIEW: SECURE AND RELIABLE VOICE RECOGNITION SYSTEM USING DEEP NEURAL NETWORKS ACOUSTIC MODEL HELMET DETECTION AND LICENSE PLATE RECOGNITION Lung…
Research Culture in Educational Institutions
My Opinion Dr.Ramesh M. KagalkarProfessor and Dean R&D,Department of Computer Science and Engineering,KLE College of Engineering and Technology, Chikod, Dist….
