{"id":164,"date":"2019-08-04T16:35:18","date_gmt":"2019-08-04T16:35:18","guid":{"rendered":"https:\/\/machinelearningindaba.com\/2017\/?page_id=164"},"modified":"2019-08-14T12:54:13","modified_gmt":"2019-08-14T12:54:13","slug":"posters","status":"publish","type":"page","link":"https:\/\/deeplearningindaba.com\/2017\/indaba\/programme\/posters\/","title":{"rendered":"Posters"},"content":{"rendered":"<h2>Poster Session Details<\/h2>\n<p>Posters are an interactive and visual way of explaining your work, getting feedback on ideas, and for meeting new people.<\/p>\n<ul>\n<li>Over the two days, there will be 154 posters presented in total.<\/li>\n<p> \u200b<\/p>\n<li>The poster session is an informal event where attendees can walk between all posters and exhibitions. It is useful to think about how you can explain the content of your poster very briefly, so that even those who aren&#8217;t working in your topic will be able to understand your motivations and learn about a different area.<\/li>\n<\/ul>\n<h4>Poster allocations<\/h4>\n<p>Every poster will be presented on either Monday or Tuesday. Find your allocation below.<\/p>\n<p><table><tr>\n\t<th>Session Date<\/th>\n\t<th>Poster Info<\/th>\n\t<\/tr><tr><td>Monday September 11th Poster Presentations<\/td><td>\n\t\t\t\t<table>\n\t\t\t\t<tr>\n\t\t\t\t<th>First Name<\/th>\n\t\t\t\t<th>Surname<\/th>\n\t\t\t\t<th>Poster Name<\/th>\n\t\t\t\t<\/tr><tr><td><\/td><td>Abbott<\/td><td>Nature inspired swarm robotics algorithms for prioritized foraging<\/td><\/tr><tr><td><\/td><td>Adebanjo<\/td><td>Feature extraction of hyperspectral images<\/td><\/tr><tr><td><\/td><td>Ajoodha<\/td><td>Computationally tracking direct influence in observational data<\/td><\/tr><tr><td><\/td><td>Atemkeng<\/td><td>Radio interferometric point spread function morphological distortion: where and why?<\/td><\/tr><tr><td><\/td><td>Bessinger<\/td><td>An integrated coastal map of South Africa<\/td><\/tr><tr><td><\/td><td>Biyela<\/td><td>-<\/td><\/tr><tr><td><\/td><td>Briers<\/td><td>River flow routing using machine learning<\/td><\/tr><tr><td><\/td><td>Chiundidza<\/td><td>Big data deep learning as an alternative for measurement of socioeconomic indicators in developing countries<\/td><\/tr><tr><td><\/td><td>Collins<\/td><td>Active learning and system identification in accelerated destructive degradation<\/td><\/tr><tr><td><\/td><td>Conway<\/td><td>Augmenting word embeddings using knowledge base data extracted from Wikipedia<\/td><\/tr><tr><td><\/td><td>Cullinan<\/td><td>Agent oriented deep learning<\/td><\/tr><tr><td><\/td><td>Currin<\/td><td>Computational neuroscience: the brain on AI<\/td><\/tr><tr><td><\/td><td>De Carvalho<\/td><td>Sales forecasting with multivariate linear regression<\/td><\/tr><tr><td><\/td><td>de Lange<\/td><td>Plant disease recognition<\/td><\/tr><tr><td><\/td><td>du Plooy<\/td><td>Applying named entity recognition on the dictionary of Southern African place names<\/td><\/tr><tr><td><\/td><td>D\u00fcsterwald<\/td><td>A computational model reveals the roles of impermeant anions and transporters in neuronal Cl- homeostasis<\/td><\/tr><tr><td><\/td><td>Earle<\/td><td>Hierarchy through composition with LMDPs<\/td><\/tr><tr><td><\/td><td>Faustine<\/td><td>Hybrid HMM-deep learning models for low-sampling energy disaggregation problem<\/td><\/tr><tr><td><\/td><td>Fick<\/td><td>Global, curve-sensitive features for offline signature verification<\/td><\/tr><tr><td><\/td><td>Gerrand<\/td><td>Deep learning for paediatric chest X-ray screening<\/td><\/tr><tr><td><\/td><td>Gilani<\/td><td>Generative adversarial networks for natural dialogue generation<\/td><\/tr><tr><td><\/td><td>Gilbert<\/td><td>NLG for isiZulu sentences using n-grams<\/td><\/tr><tr><td><\/td><td>Gobonamang<\/td><td>Intelligent DNA sub sequence repeats identification algorithm<\/td><\/tr><tr><td><\/td><td>Hamed<\/td><td>-<\/td><\/tr><tr><td><\/td><td>Henha Eyono<\/td><td>Authentication using keystroke dynamics<\/td><\/tr><tr><td><\/td><td>Hosenie<\/td><td>Source classification in deep radio surveys using machine learning techniques<\/td><\/tr><tr><td><\/td><td>James<\/td><td>Learning portable symbols for high-level planning<\/td><\/tr><tr><td><\/td><td>Jeewa<\/td><td>Cryptographically secure pseudo-random number generators using artificial neural networks<\/td><\/tr><tr><td><\/td><td>Khan<\/td><td>Neural network training optimization through reinforcement learning<\/td><\/tr><tr><td><\/td><td>Khumalo<\/td><td>Learning context for a deep recurrent neural network language model<\/td><\/tr><tr><td><\/td><td>Khumalo<\/td><td>Facial recognition<\/td><\/tr><tr><td><\/td><td>Lala<\/td><td>Unraveling the contribution of image captioning and neural machine translation for multimodal machine translation<\/td><\/tr><tr><td><\/td><td>Lebese<\/td><td>Stock market prediction using artificial neural networks and support vector machines<\/td><\/tr><tr><td><\/td><td>Liu<\/td><td>Increasing the trading prediction by mining aggregated human texting messages<\/td><\/tr><tr><td><\/td><td>Mabaso<\/td><td>Spot detection in microscopy images using convolutional neural network<\/td><\/tr><tr><td><\/td><td>Malete<\/td><td>-<\/td><\/tr><tr><td><\/td><td>Malobola<\/td><td>Intelligent process automation<\/td><\/tr><tr><td><\/td><td>Marais<\/td><td>CNNs for multi-label classification<\/td><\/tr><tr><td><\/td><td>Marom<\/td><td>-<\/td><\/tr><tr><td><\/td><td>Masakuna<\/td><td>Tackling inconsistency In classifier fusion<\/td><\/tr><tr><td><\/td><td>Maselesele<\/td><td>Having vs clustering algorithms for non stationary data streams<\/td><\/tr><tr><td><\/td><td>McCoy<\/td><td>Machine learning applications in minerals processing<\/td><\/tr><tr><td><\/td><td>Meyer<\/td><td>Applying word embedding techniques to medical data<\/td><\/tr><tr><td><\/td><td>Mmopelwa<\/td><td>Big data application on investment portfolio management and  returns prediction<\/td><\/tr><tr><td><\/td><td>Mpondo<\/td><td>Comparison of trend for segments of time series data<\/td><\/tr><tr><td><\/td><td>Msomi<\/td><td>Data driven approach to business<\/td><\/tr><tr><td><\/td><td>Mthwecu<\/td><td>Stochastic games<\/td><\/tr><tr><td><\/td><td>M\u00fcller<\/td><td>Compound landmarks for stereo-vision SLAM<\/td><\/tr><tr><td><\/td><td>Mvelase<\/td><td>Security surveillance deep learning solutions<\/td><\/tr><tr><td><\/td><td>Nekhumbe<\/td><td>Breast cancer lesion detection and segmentation using machine learning techniques<\/td><\/tr><tr><td><\/td><td>Nekoto<\/td><td>An African digital colonial museum: using deep learning, evolutionary psychology and big data tools towards a social transformation\/cultural appreciation<\/td><\/tr><tr><td><\/td><td>Nemasisi<\/td><td>Event detection on social media streams<\/td><\/tr><tr><td><\/td><td>Newman<\/td><td>Video classification using memory augmented networks<\/td><\/tr><tr><td><\/td><td>Ngejane<\/td><td>Mitigating cyber-crime and child grooming on social media using deep learning<\/td><\/tr><tr><td><\/td><td>Nimo<\/td><td>Analysis of galaxy kinematics, dynamics and evolution<\/td><\/tr><tr><td><\/td><td>Nogwanya<\/td><td>Feasibility of nuclear plasma interaction studies with the activation techniques<\/td><\/tr><tr><td><\/td><td>Oluyide<\/td><td>Unusual event detection in surveillance videos using deep learning<\/td><\/tr><tr><td><\/td><td>Perlow<\/td><td>Towards a recycling agent using novel material recognition<\/td><\/tr><tr><td><\/td><td>Peters<\/td><td>Optimal image facetting for direction dependent effects<\/td><\/tr><tr><td><\/td><td>Pise<\/td><td>Facial image analysis for e-learning<\/td><\/tr><tr><td><\/td><td>Rajohnson<\/td><td>The role of dust in star formation<\/td><\/tr><tr><td><\/td><td>Raseonyana<\/td><td>Producing an optimal examination timetable for the University of Botswana<\/td><\/tr><tr><td><\/td><td>Rens<\/td><td>Incorporating learning into an agent's stochastic knowledge management framework<\/td><\/tr><tr><td><\/td><td>Roy<\/td><td>Speech emotion recognition<\/td><\/tr><tr><td><\/td><td>Rozanova<\/td><td>Deep learning in NLP<\/td><\/tr><tr><td><\/td><td>Seedat<\/td><td>Quadcopter control<\/td><\/tr><tr><td><\/td><td>Sejeso<\/td><td>-<\/td><\/tr><tr><td><\/td><td>Setlhake<\/td><td>Deep learning in multi-spectral image classification<\/td><\/tr><tr><td><\/td><td>Shabalala<\/td><td>Violence detection and characterization in surveillance videos<\/td><\/tr><tr><td><\/td><td>Sooknunan<\/td><td>Optical\/radio transient classification with machine learning<\/td><\/tr><tr><td><\/td><td>Thompson<\/td><td>The use of contour integrals for error estimation in Gauss quadrature<\/td><\/tr><tr><td><\/td><td>Torpey<\/td><td>Human action recognition using recurrent neural networks<\/td><\/tr><tr><td><\/td><td>Toussaint<\/td><td>A knowledge-centric approach to modelling dynamic customer segmentation in domestic load research<\/td><\/tr><tr><td><\/td><td>van der Walt<\/td><td>Are the mysterious dryland \"Fairy Circles\" the result of microbial phytopathogenesis?<\/td><\/tr><tr><td><\/td><td>Vos<\/td><td>Machine learning in astronomy<\/td><\/tr><tr><td><\/td><td>Woodford<\/td><td>The concurrent development of neural network based simulators and controllers in the evolutionary robotics process<\/td><\/tr><tr><td><\/td><td>Zangwa<\/td><td>Development of an algorithm for automatic segmentation of foliage images from uncontrolled environment<\/td><\/tr><\/table><\/td><\/tr><tr><td>Tuesday September 12th Poster Presentations<\/td><td>\n\t\t\t\t<table>\n\t\t\t\t<tr>\n\t\t\t\t<th>First Name<\/th>\n\t\t\t\t<th>Surname<\/th>\n\t\t\t\t<th>Poster Name<\/th>\n\t\t\t\t<\/tr><tr><td><\/td><td>Alhassan<\/td><td>Radio sources classification with machine learning techniques<\/td><\/tr><tr><td><\/td><td>Amima<\/td><td>Applications of machine learning to identify differently expressed genes in breast cancer patients<\/td><\/tr><tr><td><\/td><td>Angulu<\/td><td>Hierarchical age estimation using facial features<\/td><\/tr><tr><td><\/td><td>Aniyan<\/td><td>Deep learning for radio astronomy<\/td><\/tr><tr><td><\/td><td>Arthur<\/td><td>Thermal hydraulics and transient analysis of a nuclear research reactor using CFD code<\/td><\/tr><tr><td><\/td><td>Ayami<\/td><td>Improving facial recognition algorithms with an application to DUT security<\/td><\/tr><tr><td><\/td><td>Bayana<\/td><td>Gender classification based on feature fusion<\/td><\/tr><tr><td><\/td><td>Bester<\/td><td>Model-based reinforcement learning with parameterised action spaces<\/td><\/tr><tr><td><\/td><td>Booyse<\/td><td>Recurrent neural networks for asset failure prediction<\/td><\/tr><tr><td><\/td><td>Breytenbach<\/td><td>On the use of neural networks for classifying time series<\/td><\/tr><tr><td><\/td><td>Chibuye<\/td><td>Low-resource language speech recognition using cross-language phoneme mapping<\/td><\/tr><tr><td><\/td><td>Chingozha<\/td><td>Stabilisability preserving abstractions of control systems<\/td><\/tr><tr><td><\/td><td>Chougrad<\/td><td>A deep learning framework for breast cancer screening<\/td><\/tr><tr><td><\/td><td>Daud<\/td><td>Disability, brain control and ML<\/td><\/tr><tr><td><\/td><td>de Wet<\/td><td>Automatic recognition of code-switched South African speech<\/td><\/tr><tr><td><\/td><td>du Toit<\/td><td>A comparative evaluation and analysis of open-source part-of-speech taggers for under resourced official South African languages<\/td><\/tr><tr><td><\/td><td>Dufourq<\/td><td>Deep neural network architecture optimisation<\/td><\/tr><tr><td><\/td><td>Egbelowo<\/td><td>-<\/td><\/tr><tr><td><\/td><td>El Bouchefry<\/td><td>Astrophysical machine learning software: an overview<\/td><\/tr><tr><td><\/td><td>Gouaya<\/td><td>Face recognition using HOSVD<\/td><\/tr><tr><td><\/td><td>Grunow<\/td><td>Full 3+1 dimensional simulation of the Boltzmann equation in the context of heavy ion collisions<\/td><\/tr><tr><td><\/td><td>Gueorguiev<\/td><td>ASTCVS: a cognitive vision system for astronomical phenomenon classification<\/td><\/tr><tr><td><\/td><td>Hasani<\/td><td>Learning and modeling analog behavior<\/td><\/tr><tr><td><\/td><td>Hooper<\/td><td>Acting under partial information in virtual worlds<\/td><\/tr><tr><td><\/td><td>Ikram<\/td><td>Using deep learning with community detection to solve the cold start problem in recommender systems<\/td><\/tr><tr><td><\/td><td>Jain<\/td><td>-<\/td><\/tr><tr><td><\/td><td>Josias<\/td><td>Identifying vein intersections in Tsetse fly wing images<\/td><\/tr><tr><td><\/td><td>Keivani<\/td><td>Tracking moving objects in dynamic scenes<\/td><\/tr><tr><td><\/td><td>Kekere<\/td><td>Incremental learning for big data<\/td><\/tr><tr><td><\/td><td>Khoza<\/td><td>A spiking neural network approach to natural language processing<\/td><\/tr><tr><td><\/td><td>Knowles<\/td><td>GMRT diffuse radio emission cluster survey<\/td><\/tr><tr><td><\/td><td>Kohlakala<\/td><td>Human ear recognition based on global features<\/td><\/tr><tr><td><\/td><td>Lai Hong<\/td><td>Adaptive knowledge injection for Monte Carlo tree search<\/td><\/tr><tr><td><\/td><td>Lambo<\/td><td>Deep reinforcement learning for games of perfect information<\/td><\/tr><tr><td><\/td><td>Makati<\/td><td>Semi-automated detectable life band<\/td><\/tr><tr><td><\/td><td>Manabe<\/td><td>African Solutions to Meet SDG 7: Affordable and Clean Energy<\/td><\/tr><tr><td><\/td><td>Marumo<\/td><td>Data analytic framework for radio astronomy: hierarchical artifact detection (HArD)<\/td><\/tr><tr><td><\/td><td>Maseko<\/td><td>Optimized path planning and path tracking for autonomous vehicles with a constrained turning rate<\/td><\/tr><tr><td><\/td><td>Mbonda Tiekwe<\/td><td>-<\/td><\/tr><tr><td><\/td><td>Modupe<\/td><td>-<\/td><\/tr><tr><td><\/td><td>Moiloa<\/td><td>Segmentation of low contrast time based neural fluorescence images<\/td><\/tr><tr><td><\/td><td>Mokoena<\/td><td>Anomaly explanations<\/td><\/tr><tr><td><\/td><td>Moodley<\/td><td>-<\/td><\/tr><tr><td><\/td><td>Mostert<\/td><td>Calibration of stochastic processes using neural networks<\/td><\/tr><tr><td><\/td><td>Motsoehli<\/td><td>Use of spark streaming and gradient boosting to identify application fraud in the retail space in realtime<\/td><\/tr><tr><td><\/td><td>Mpipi<\/td><td>Predicting students performance using machine learning<\/td><\/tr><tr><td><\/td><td>Mtetwa<\/td><td>Brain MRI structure segementation<\/td><\/tr><tr><td><\/td><td>Muleya<\/td><td>Multiscale modeling TB transmission dynamics<\/td><\/tr><tr><td><\/td><td>Mvubu<\/td><td>Financial market time series prediction with Long Short Term Memory (LSTM's)<\/td><\/tr><tr><td><\/td><td>Ndlovu<\/td><td>Stereo image and 3D point cloud mapping and localisation for self-driving cars in outdoor unstructured environments<\/td><\/tr><tr><td><\/td><td>Newman<\/td><td>Classifying sleep stages from wearable data<\/td><\/tr><tr><td><\/td><td>Nguyen<\/td><td>Learning to rank from clicks: a probabilistic model for separating relevance from positional bias in search logs<\/td><\/tr><tr><td><\/td><td>Niit<\/td><td>Applications of reinforcement learning to psychiatric disorders<\/td><\/tr><tr><td><\/td><td>Nyambal<\/td><td>Automatic parking space detection based on convolutional neural networks and support vector machines<\/td><\/tr><tr><td><\/td><td>Ofosu Mensah<\/td><td>Investigating relationship between expressed cancer related genes and patient survival<\/td><\/tr><tr><td><\/td><td>Okouma<\/td><td>A new deterministic scheme for characterizing the organization of (large) prime numbers<\/td><\/tr><tr><td><\/td><td>Oldewage<\/td><td>Particle swarm optimization in high dimensional spaces<\/td><\/tr><tr><td><\/td><td>Perez<\/td><td>Supporting the fight against human trafficking<\/td><\/tr><tr><td><\/td><td>Pretorius<\/td><td>Learning dynamics of neural networks in reinforcement learning<\/td><\/tr><tr><td><\/td><td>Radulescu<\/td><td>Whole body locomotion planning for quadrupedal systems<\/td><\/tr><tr><td><\/td><td>Rajaram<\/td><td>Generative adversarial networks<\/td><\/tr><tr><td><\/td><td>Ranchod<\/td><td>Skill discovery in reinforcement learning<\/td><\/tr><tr><td><\/td><td>Rapheeha<\/td><td>Artificial neural network<\/td><\/tr><tr><td><\/td><td>Rice<\/td><td>Discrete mathematics intelligent tutoring system using Bayesian networks<\/td><\/tr><tr><td><\/td><td>Schuld<\/td><td>Machine learning on quantum computers<\/td><\/tr><tr><td><\/td><td>Sefala<\/td><td>3D convolutions for action recognition<\/td><\/tr><tr><td><\/td><td>Sihlangu<\/td><td>Cognitive MeerKat<\/td><\/tr><tr><td><\/td><td>Sithole<\/td><td>Big data and loT<\/td><\/tr><tr><td><\/td><td>Steyn<\/td><td>Short-term stream flow forecasting at Australian river sites using data-driven regression techniques<\/td><\/tr><tr><td><\/td><td>Takong<\/td><td>Investigating rainfall spatial variability over the Drakensberg Mountain Range using artificial neural networks<\/td><\/tr><tr><td><\/td><td>Tavakoli<\/td><td>Deep reinforcement learning for robot learning<\/td><\/tr><tr><td><\/td><td>Umuhire<\/td><td>Development of a post-processing technique for a quantum key distribution system<\/td><\/tr><tr><td><\/td><td>van Biljon<\/td><td>The creation of intelligent agents with machine learning<\/td><\/tr><tr><td><\/td><td>van Niekerk<\/td><td>Direct sampling using the discrete pulse transform<\/td><\/tr><tr><td><\/td><td>van Niekerk<\/td><td>Online constrained model-based reinforcement learning<\/td><\/tr><tr><td><\/td><td>Zitha<\/td><td>Fine-tuning radio calibration using machine learning methods<\/td><\/tr><tr><td><\/td><td>Zwane<\/td><td>Robot multi-tasking using deep reinforcement learning from raw RGBDT data (T for tactile sensor data)<\/td><\/tr><\/table><\/td><\/tr><\/table><\/p>\n<h3>Poster Preparation and Prizes<\/h3>\n<ul>\n<li>Poster size: Should be A0 size, in either landscape or portrait mode.<\/li>\n<li>Poster printing: We suggest you print your poster in advance and bring it with you. <\/li>\n<p>\u200b<\/p>\n<li>If you need inspiration in designing a poster, try looking <a href=\"https:\/\/www.ncbi.nlm.nih.gov\/pmc\/articles\/PMC1876493\/\" rel=\"noopener noreferrer\" target=\"_blank\">here<\/a> or <a href=\"http:\/\/hsp.berkeley.edu\/sites\/default\/files\/ScientificPosters.pdf\" rel=\"noopener noreferrer\" target=\"_blank\">here<\/a> for some advice.<\/li>\n<\/ul>\n<p><div><h3>Prizes!<\/h3><p><p>We want everyone to have fun at these events, but also to encourage people to do their best work. The best posters will receive prizes for their efforts. We have these prizes, and a few other secret prizes to be awarded on the final night to those posters and presenters that have shined. <\/p>\n<\/p><div class=\"single_prize\"><div class=\"prize_giver_img\"><img decoding=\"async\"  src=\"https:\/\/deeplearningindaba.com\/2017\/wp-content\/uploads\/sites\/2\/2019\/08\/nvidia.jpg\"\/><\/div><div class=\"prize_giver\"><h5>NVIDIA<\/h5><\/div><div class='ind_prize'><img decoding=\"async\"  src=\"https:\/\/deeplearningindaba.com\/2017\/wp-content\/uploads\/sites\/2\/2019\/08\/titan.jpg\"\/><\/div><\/div><div class=\"single_prize\"><div class=\"prize_giver_img\"><img decoding=\"async\"  src=\"https:\/\/deeplearningindaba.com\/2017\/wp-content\/uploads\/sites\/2\/2019\/08\/997703947.jpg\"\/><\/div><div class=\"prize_giver\"><h5>Cambridge University Press<\/h5><\/div><div class='ind_prize'><img decoding=\"async\"  src=\"https:\/\/deeplearningindaba.com\/2017\/wp-content\/uploads\/sites\/2\/2019\/08\/machine-learning-refined.jpg\"\/><img decoding=\"async\"  src=\"https:\/\/deeplearningindaba.com\/2017\/wp-content\/uploads\/sites\/2\/2019\/08\/computer-age-statistical-inference.jpg\"\/><img decoding=\"async\"  src=\"https:\/\/deeplearningindaba.com\/2017\/wp-content\/uploads\/sites\/2\/2019\/08\/bayesian-reasoning-and-machine-learning.jpg\"\/><\/div><\/div><div class=\"single_prize\"><div class=\"prize_giver_img\"><img decoding=\"async\"  src=\"https:\/\/deeplearningindaba.com\/2017\/wp-content\/uploads\/sites\/2\/2019\/08\/mit.png\"\/><\/div><div class=\"prize_giver\"><h5>MIT press online<\/h5><\/div><div class='ind_prize'><img decoding=\"async\"  src=\"https:\/\/deeplearningindaba.com\/2017\/wp-content\/uploads\/sites\/2\/2019\/08\/dl.jpg\"\/><img decoding=\"async\"  src=\"https:\/\/deeplearningindaba.com\/2017\/wp-content\/uploads\/sites\/2\/2019\/08\/ml.jpg\"\/><\/div><\/div><\/div><\/p>\n<p>If there is anything we can clarify, please reach out to us at: <a href=\"mailto:dl-indaba@googlegroups.com\" rel=\"noopener noreferrer\" target=\"_blank\">dl-indaba@googlegroups.com<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Poster Session Details Posters are an interactive and visual way of explaining your work, getting feedback on ideas, and for meeting new people. Over the two days, there will be 154 posters presented in total. \u200b The poster session is an informal event where attendees can walk between all posters and exhibitions. It is useful [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":176,"parent":170,"menu_order":5,"comment_status":"closed","ping_status":"closed","template":"pt-indaba-old.php","meta":{"_acf_changed":false,"footnotes":"","_links_to":"","_links_to_target":""},"class_list":["post-164","page","type-page","status-publish","has-post-thumbnail","hentry"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.3 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Posters - Deep Learning Indaba 2017<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/deeplearningindaba.com\/2017\/indaba\/programme\/posters\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Posters - Deep Learning Indaba 2017\" \/>\n<meta property=\"og:description\" content=\"Poster Session Details Posters are an interactive and visual way of explaining your work, getting feedback on ideas, and for meeting new people. Over the two days, there will be 154 posters presented in total. \u200b The poster session is an informal event where attendees can walk between all posters and exhibitions. 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