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This paper presents a cursive character recognizer, a crucial module in any Cursive Script Recognition system based on a segmentation and recognition approach. The character classification is achieved by combining the use of Neural Gas (NG) and Learning Ve ...
This paper presents a survey on Off-Line Cursive Script Recognition. The approaches to the problem are described into detail. Each step of the process leading from raw data to the final result is analyzed.\ This survey is divided into two parts, the first ...
This paper presents an energy-aware method for recognizing time series acceleration data containing both activities and gestures using a wearable device coupled with a smartphone. In our method, we use a small wearable device to collect accelerometer data ...
We propose fingerprinting, a new technique that consists in constructing compact, fast-to-compute and privacy-preserving binary representations of datasets. We illustrate the effectiveness of our approach on the emblematic big data problem of K-Nearest-Nei ...
This work presents an Offline Cursive Word Recognition System dealing with single writer samples. The system is a continuous density hiddden Markov model trained using either the raw data, or data transformed using Principal Component Analysis or Independe ...
Dataset for the manuscript "Lithium tantalate photonic integrated circuits for volume manufacturing". DOI: 10.1038/s41586-024-07369-1 Contains all raw data and code used to produce the Figures and Extended Data Figures in the manuscript. ...
This work presents an Offline Cursive Word Recognition System dealing with single writer samples. The system is a continuous density hiddden Markov model trained using either the raw data, or data transformed using Principal Component Analysis or Independe ...
This paper presents a cursive character recognizer, a crucial module in any Cursive Script Recognition system based on a segmentation and recognition approach. The character classification is achieved by combining the use of Neural Gas (NG) and Learning Ve ...
