Multi-object tracking aims to locate and track all objects in a video feed. It’s a fundamental component in domains like mobile robots, where an autonomous system must navigate dynamic surroundings…
Read MoreBayesian (deep) learning has always intrigued and intimidated me. Perhaps because it leans heavily on probabilistic theory, which can be daunting. I noticed that even though I knew basic probability…
Read MoreHugging Face is one of the most promising companies in the world. It has set to achieve a unique feat – to become the GitHub for machine learning. Over the…
Read MoreBy partnering with Google, DeepMind is able to bring the benefits of AI to billions of people all over the world. From reuniting a speech-impaired user with his original voice, to…
Read MoreApplying bayesian on neural networks is a method of controlling overfitting. We can also apply bayesian on CNN to reduce the overfitting and we can call CNN with applied Bayesian…
Read MoreContext-awareness is an important characteristic of smart home. Several methods are used in context-aware application to provide services. The main target of smart home is to predict the demand of…
Read MoreThe new Internet of Things (IoT) technology has the potential to generate breakthrough opportunities in real-life applications. The merger of IoT with other technologies like context-aware computing, big data, artificial…
Read MoreBy using hypernetworks, researchers can now preemptively fine-tune artificial neural networks, saving some of the time and expense of training. Artificial intelligence is largely a numbers game. When deep neural…
Read MoreRecognition of activities from sensors is a key paradigm of ubiquitous computing. Activity recognition systems can be used to label large sets of data. Variability in human activities, sensor deployment…
Read MoreIn recent decades,attention has been focused on analyzing contextual data in educational contextusingeducational data mining (EDM), which is a process of employing data mining techniques to transform initial data collected…
Read MoreStock market prices are known to be very volatile and noisy, and their accurate forecasting is a challenging problem. Traditionally, both linear and non-linear methods (such as ARIMA and LSTM)…
Read MoreStock prediction is a very hot topic in our life. However, in the early time, because ofsome reasons and the limitation of the device, only a few people had the…
Read MoreStock market trading is an activity in which investors need fast and accurate information to make effectivedecisions. Since many stocks are traded on a stock exchange, numerous factors influence the…
Read MoreREVIEW: SECURE AND RELIABLE VOICE RECOGNITION SYSTEM USING DEEP NEURAL NETWORKS ACOUSTIC MODEL HELMET DETECTION AND LICENSE PLATE RECOGNITION Lung cancer classification with Convolutional Neural Network Architectures APPLICATION OF CONVOLUTIONAL…
Read MoreMy Opinion Dr.Ramesh M. KagalkarProfessor and Dean R&D,Department of Computer Science and Engineering,KLE College of Engineering and Technology, Chikod, Dist. Belagavi, Karnataka, India "The engineer's first problem in any design…
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