output
19972026
most citedApplications of Deep Learning and Reinforcement Learning to Biological Data

876 citations

Showing 2018Show all

9 papers · 1 filter

cs.GT2018

Collective Strategies with a Master-slave Mechanism Dominate in Spatial Iterated Prisoner's Dilemma

Jiawei Li, etc

How cooperation emerges and persists in a population of selfish agents is a fundamental question in evolutionary game theory. Our research shows that Collective Strategies with Mas…

cs.CV2018★ 1 cited

Saliency Detection via Bidirectional Absorbing Markov Chain

Fengling Jiang, Bin Kong, Ahsan Adeel +2

Traditional saliency detection via Markov chain only considers boundaries nodes. However, in addition to boundaries cues, background prior and foreground prior cues play a compleme…

cs.CR2018★ 4 cited

Statistical Analysis Driven Optimized Deep Learning System for Intrusion Detection

Cosimo Ieracitano, Ahsan Adeel, Mandar Gogate +5

Attackers have developed ever more sophisticated and intelligent ways to hack information and communication technology systems. The extent of damage an individual hacker can carry…

cs.CL2018★ 3 cited

SentiALG: Automated Corpus Annotation for Algerian Sentiment Analysis

Imane Guellil, Ahsan Adeel, Faical Azouaou +1

Data annotation is an important but time-consuming and costly procedure. To sort a text into two classes, the very first thing we need is a good annotation guideline, establishing…

cs.CL2018★ 11 cited

Exploiting Deep Learning for Persian Sentiment Analysis

Kia Dashtipour, Mandar Gogate, Ahsan Adeel +3

The rise of social media is enabling people to freely express their opinions about products and services. The aim of sentiment analysis is to automatically determine subject's sent…

cs.SD2018★ 45 cited

DNN driven Speaker Independent Audio-Visual Mask Estimation for Speech Separation

Mandar Gogate, Ahsan Adeel, Ricard Marxer +2

Human auditory cortex excels at selectively suppressing background noise to focus on a target speaker. The process of selective attention in the brain is known to contextually expl…