OnionMHC: A deep learning model for peptide
The model can be used in the screening of potential neo-epitopes for the development of cancer vaccines or designing peptides for peptide-based therapeutics.
The model can be used in the screening of potential neo-epitopes for the development of cancer vaccines or designing peptides for peptide-based therapeutics.
Deep neural networks (DNNs) have become an important tool in solving various problems in numerous disciplines. However, DNNs are also known for their high resource requirement, weight redundancy, and large-scale parameters.
Consistent changes come up every day like online classes, digital books, kindle editions etc. But changes like this rarely thought about how much it’s efficient or the user understands the concept in the book or paper.
A smart mirror is a system that functions as mirror with additionally capability of displaying Weather details, News, Date & Time, and Calendar.
With ever increasing cases of various types of spoof attacks, and due to vulnerabilities present in the existing systems different biometric modalities have been explored and EEG is one of them.
The use of deep learning models in edge-devices is still limited. Deploying a large model onto small devices for real-time inference requires an adequate amount of resources.
Deep neural networks (DNNs) have become an important tool in solving various problems in numerous disciplines. However, DNNs are also known for their high resource requirement, weight redundancy, and large-scale parameters.
Corona virus more popularly known as COVID-19 is an extremely virulent strain from the Corona virus family of viruses and their origin is attributed to bats and civet cats.
DataStream mining is a challenging task for researchers because of the change in data distribution during classification, known as concept drift. Drift detection algorithms emphasize detecting the drift.
Due to the physical restriction of current CMOS technology, emerging technologies that have majority logic gate as a base component are being explored. The process of transforming from boolean network to the majority logic network is called majority logic synthesis (MLS).
A significant progress has been made in automated medical diagnosis with the advent of deep learning methods in recent years. However, deploying a deep learning model for mobile and small-scale, low-cost devices is a major bottleneck.
COVID-19 has become a pandemic for the entire world, and it has significantly affected the world economy. The importance of early detection and treatment of the infection cannot be overstated.
Deep neural networks (DNNs) have become an important tool in solving various problems in numerous disciplines. However, DNNs are also known for their high resource requirement, weight redundancy, and large-scale parameters.
Representations of the (Lorentz) conformal group with the soft operators as highest weight vectors have two universal properties, which we clearly state in this paper.
Soft operators are (roughly speaking) zero energy massless particles which live on the celestial sphere in Minkowski space.
In this paper we evaluate the modified celestial amplitude for gravitons and gluons, as defined in [4]. We find that the modified (tree) amplitude is finite for gravitons in Einstein gravity.
In recent years, machine learning (ML) and deep learning (DL) have shown remarkable improvement in computer vision, natural language processing, stock prediction, forecasting, and audio processing to name a few.
Ensemble Classifier provides a promising way to improve the accuracy of classification for sentiment analysis and opinion mining.
Pot-holes on road will make transportation slower and costly. India has a big network of roads to connect the villages and cities.
Ensemble classifiers are showing a promising way to solve various classification and predictive problems.
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