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As a member of our engineering team, you will develop new features for our AI-driven assistant to help make workers better at their jobs...
Talla is looking for a blockchain software engineer with experience building innovative services and technologies to help Talla incorporate blockchain & cryptocurrency functionality into their intelligent automation bot platform.
As a member of our data science team, you will be responsible for data-driven improvements to our natural language processing models. You will work to improve our knowledge creation, management, and delivery technologies.
As Lead Data Scientist, you will be responsible for driving the research direction and application of technologies such as neural information retrieval, semantic parsing, and knowledge extraction and representation.
Currently, Segmentation of bitewing radiograpy images is a very challengingtask. The focus of the study is to segment it into caries, enamel, dentin,pulp, crowns, restoration and root canal treatments. The main method ofsemantic segmentation of bitewing radiograpy images at this stage is theU-shaped...
The application resource specification--a static specification of severalparameters such as the number of threads and the scratchpad memory usage perthread block--forms a critical component of the existing GPU programmingmodels. This specification determines the performance of the application...
Traditional methods in Chinese typography synthesis view characters as anassembly of radicals and strokes, but they rely on manual definition of the keypoints, which is still time-costing. Some recent work on computer visionproposes a brand new approach: to treat every Chinese character as...
Driven by successes in deep learning, computer vision research has begun tomove beyond object detection and image classification to more sophisticatedtasks like image captioning or visual question answering. Motivating suchendeavors is the desire for models to capture not only objects present in...
Although deep neural networks have made tremendous progress in the area ofmultimedia representation, training neural models requires a large amount ofdata and time. It is well-known that utilizing trained models as initialweights often achieves lower training error than neural networks that are...
When submitting queries to information retrieval (IR) systems, users oftenhave the option of specifying which, if any, of the query terms are heavilydependent on each other and should be treated as a fixed phrase, for instanceby placing them between quotes. In addition to such cases where users...
We present an efficient learning-based algorithm for deformable, pairwise 3Dmedical image registration. Current registration methods optimize an energyfunction independently for each pair of images, which can be time-consuming forlarge data. We define registration as a parametric function, and...
In this paper, we are mainly concerned with the ability to quickly andautomatically distinguish word senses in dynamic semantic spaces in which newterms and new senses appear frequently. Such spaces are built '"on the fly"from constantly evolving data sets such as Wikipedia, repositories of...
Automatic speech recognition (ASR) systems lack joint optimization duringdecoding over the acoustic, lexical and language models; for instance the ASRwill often prune words due to acoustics using short-term context, prior torescoring with long-term context. In this work we model the automated...
In the last decade, special purpose computing systems, such as Neuromorphiccomputing, have become very popular in the field of computer vision and machinelearning for classification tasks. In 2015, IBM's released the TrueNorthNeuromorphic system, kick-starting a new era of Neuromorphic computing...
Spatial pyramid pooling module or encode-decoder structure are used in deepneural networks for semantic segmentation task. The former networks are able toencode multi-scale contextual information by probing the incoming features withfilters or pooling operations at multiple rates and multiple...
Ubuntu dialogue corpus is the largest public available dialogue corpus tomake it feasible to build end-to-end deep neural network models directly fromthe conversation data. One challenge of Ubuntu dialogue corpus is the largenumber of out-of-vocabulary words. In this paper we proposed a method...
Deep learning, and in particular Recurrent Neural Networks (RNN) have shownsuperior accuracy in a large variety of tasks including machine translation,language understanding, and movie frame generation. However, these deeplearning approaches are very expensive in terms of computation. In most cases...
Automatic feature extraction using neural networks has accomplishedremarkable success for images, but for sound recognition, these models areusually modified to fit the nature of the multi-dimensional temporalrepresentation of the audio signal in spectrograms. This may not efficientlyharness the...
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