Machine learning for transient recognition in difference imaging with minimum sampling effort
نویسندگان
چکیده
منابع مشابه
Machine learning based Visual Evoked Potential (VEP) Signals Recognition
Introduction: Visual evoked potentials contain certain diagnostic information which have proved to be of importance in the visual systems functional integrity. Due to substantial decrease of amplitude in extra macular stimulation in commonly used pattern VEPs, differentiating normal and abnormal signals can prove to be quite an obstacle. Due to developments of use of machine l...
متن کاملTemporal-difference Learning with Sampling Baseline for Image Captioning
The existing methods for image captioning usually train the language model under the cross entropy loss, which results in the exposure bias and inconsistency of evaluation metric. Recent research has shown these two issues can be well addressed by policy gradient method in reinforcement learning domain attributable to its unique capability of directly optimizing the discrete and non-differentia...
متن کاملMachine Learning for Activity Recognition
This paper surveys the activity recognition task from a machine learning perspective. I give a definition of this problem, and I classify different activity recognition problems into two categories. I show the activities can be hierarchical, and based on such hierarchies I synthesize a language to describe activities. I give a general criteria set to evaluate activity recognition methods. I sum...
متن کاملMachine Learning for Plan Recognition
action subsuming make spaghetti and make fettucini (make pesto and make marinara). Edge labels like h=; 1; 2i represent between two actions a and b represent the fact that the rst argument of a is identical to the second argument of b. Computing the join of G1 and G2 then consists of nding action nodes sharing a common abstraction and identifying temporal and strcutural relations common to both...
متن کاملOnline Learning for Effort Reduction in Interactive Neural Machine Translation
Neural machine translation systems require large amounts of training data and resources. Even with this, the quality of the translations may be insufficient for some users or domains. In such cases, the output of the system must be revised by a human agent. This can be done in a post-editing stage or following an interactive machine translation protocol. We explore the incremental update of neu...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Monthly Notices of the Royal Astronomical Society
سال: 2020
ISSN: 0035-8711,1365-2966
DOI: 10.1093/mnras/staa3096