公开(公告)号：US10891524B2

公开(公告)日：2021-01-12

申请号：US16017742

申请日：2018-06-25

Applicant: Nokia Technologies Oy

Inventor： Mikko Honkala ,  Francesco Cricri ,  Xingyang Ni

IPC: G06K9/62 ,  G06K9/72 ,  G06N3/08 ,  G06N3/04

Abstract: The invention relates to a method comprising receiving a set of input samples, said set of input images comprising real images and generated images; extracting a set of feature maps from multiple layers of a pre-trained neural network for both the real images and the generated images; determining statistics for each feature map of the set of feature maps; comparing statistics of the feature maps for the real images to statistics of the feature maps for the generated images by using a distance function to obtain a vector of distances; and averaging the distances of the vector of distances to have a value indicating a diversity of the generated images. The invention also relates to technical equipment for implementing the method.

公开(公告)号：US20190325887A1

公开(公告)日：2019-10-24

申请号：US15956457

申请日：2018-04-18

Applicant: Nokia Technologies Oy

Inventor： Asta Maria Karkkainen ,  Leo Mikko Johannes Karkkainen ,  Mikko Honkala ,  Sampo Vesa

IPC: G10L21/0208 ,  G10K11/16

Abstract: A method includes accessing, by at least one processing device, an audible signal including at least one in-ear microphone audible signal and at least one external microphone audible signal and at least one noise signal; training a generative network to generate an enhanced external microphone signal from an in-ear microphone signal based on the at least one in-ear microphone audible signal and the at least one external microphone audible signal; and outputting the generative network.

公开(公告)号：US20190251360A1

公开(公告)日：2019-08-15

申请号：US16342084

申请日：2017-09-27

Applicant: Nokia Technologies Oy

Inventor： Francesco Cricri ,  Mikko Honkala ,  Emre Baris Aksu ,  Xingyang Ni

IPC: G06K9/00 ,  G06K9/62 ,  G06N3/04

CPC classification number: G06K9/00744 ,  G06K9/00664 ,  G06K9/00711 ,  G06K9/4628 ,  G06K9/6234 ,  G06N3/04 ,  G06N3/0445 ,  G06N3/0454

Abstract: The invention relates to a method, an apparatus and a computer program product for analyzing media content. The method comprises receiving media content; performing feature extraction of the media content at a plurality of convolution layers to produce a plurality of layer-specific feature maps; transmitting from the plurality of convolution layers a corresponding layer-specific feature map to a corresponding de-convolution layer of a plurality of de-convolution layers via a recurrent connection between the plurality of convolution layers and the plurality of de-convolution layers; and generating a reconstructed media content based on the plurality of feature maps.

公开(公告)号：US12142014B2

公开(公告)日：2024-11-12

申请号：US17430987

申请日：2020-01-29

Applicant: Nokia Technologies Oy

Inventor： Caglar Aytekin ,  Francesco Cricri ,  Mikko Honkala

IPC: G06T9/00 ,  G06N3/08 ,  H04N19/132 ,  H04N19/15 ,  H04N19/196

Abstract: The embodiments relate to a method comprising compressing input data (I) by means of at least a neural network (E, 310); determining a compression rate for data compression; miming the neural network (E, 310) with the input data (I) to produce an output data (c); removing a number of elements from the output data (c) according to the compression rate to result in a reduced form of the output data (me); and providing the reduced form of the output data (me) and the compression rate to a decoder (D, 320). The embodiments also relate to a method comprising receiving input data (me) for decompression; decompressing the input data (me) by means of at least a neural network (D, 320); determining a decompression rate for decompressing the input data (me); miming the neural network (D, 320) with input data (me) to produce a decompressed output data (ĩ); padding a number of elements to the compressed input data (me) according to the decompression rate to produce an output data (ĩ); and providing the output data (ĩ).

公开(公告)号：US11622119B2

公开(公告)日：2023-04-04

申请号：US17575946

申请日：2022-01-14

Applicant: Nokia Technologies Oy

Inventor： Miska Hannuksela ,  Mikko Honkala ,  Jani Lainema ,  Francesco Cricri ,  Emre Aksu

IPC: H04N19/176 ,  H04N19/149 ,  H04N19/436 ,  H04N19/65 ,  G06N3/08

Abstract: A method includes maintaining a set of parameters or weights derived through online learning for a neural net; transmitting an update of the parameters or weights to a decoder; deriving a first prediction block based on an output of the neural net using the parameters or weights; deriving a first encoded prediction error block through encoding a difference of the first prediction block and a first input block; encoding the first encoded prediction error block into a bitstream; deriving a reconstructed prediction error block based on the first encoded prediction error block; deriving a second prediction block based on an output of the neural net using the parameters or weights and the reconstructed prediction error block; deriving a second encoded prediction error block through encoding a difference of the second prediction block and a second input block; and encoding the second encoded prediction error block into a bitstream.

公开(公告)号：US20220141471A1

公开(公告)日：2022-05-05

申请号：US17575946

申请日：2022-01-14

Applicant: Nokia Technologies Oy

Inventor： Miska HANNUKSELA ,  Mikko Honkala ,  Jani Lainema ,  Francesco Cricri ,  Emre Aksu

IPC: H04N19/149 ,  H04N19/176 ,  H04N19/436 ,  H04N19/65 ,  G06N3/08

Abstract: A method includes maintaining a set of parameters or weights derived through online learning for a neural net; transmitting an update of the parameters or weights to a decoder; deriving a first prediction block based on an output of the neural net using the parameters or weights; deriving a first encoded prediction error block through encoding a difference of the first prediction block and a first input block; encoding the first encoded prediction error block into a bitstream; deriving a reconstructed prediction error block based on the first encoded prediction error block; deriving a second prediction block based on an output of the neural net using the parameters or weights and the reconstructed prediction error block; deriving a second encoded prediction error block through encoding a difference of the second prediction block and a second input block; and encoding the second encoded prediction error block into a bitstream.

公开(公告)号：US11241198B2

公开(公告)日：2022-02-08

申请号：US16332256

申请日：2016-09-20

Applicant: Nokia Technologies Oy

Inventor： Kim Blomqvist ,  Mikko Honkala ,  Harri Lindholm

IPC: A61B5/00 ,  A61B5/0535 ,  A61B5/349 ,  A61B5/366

Abstract: An approach is provided for synchronizing an impedance cardiography (“ICG”) measurement period with an electrocardiography (“ECG”) signal to reduce patient (105) auxiliary current. The approach involves measuring an ECG signal of a patient via an ECG device (103). The approach also involves processing the ECG signal to cause, at least in part, a detection of one or more ECG features of the signal. The approach further involves synchronizing a start, a stop, or a combination thereof of a measurement of an ICG signal of the patient via an ICG device (101) based, at least in part, on the detection of the one or more ECG features. The measurement of the ICG signal includes injecting an electrical current into the patient (105) for a duration of the measurement.

公开(公告)号：US11068722B2

公开(公告)日：2021-07-20

申请号：US16342084

申请日：2017-09-27

Applicant: Nokia Technologies Oy

Inventor： Francesco Cricri ,  Mikko Honkala ,  Emre Baris Aksu ,  Xingyang Ni

IPC: G06K9/46 ,  G06N3/04 ,  G06K9/62 ,  G06K9/00

Abstract: The invention relates to a method, an apparatus and a computer program product for analyzing media content. The method comprises receiving media content; performing feature extraction of the media content at a plurality of convolution layers to produce a plurality of layer-specific feature maps; transmitting from the plurality of convolution layers a corresponding layer-specific feature map to a corresponding de-convolution layer of a plurality of de-convolution layers via a recurrent connection between the plurality of convolution layers and the plurality of de-convolution layers; and generating a reconstructed media content based on the plurality of feature maps.

公开(公告)号：US20210195206A1

公开(公告)日：2021-06-24

申请号：US16771115

申请日：2018-12-03

Applicant: Nokia Technologies Oy

Inventor： Miska Hannuksela ,  Mikko Honkala ,  Jani Lainema ,  Francesco Cricri ,  Emre Aksu

IPC: H04N19/149 ,  H04N19/65 ,  H04N19/436 ,  H04N19/176 ,  G06N3/08

Abstract: A method comprising: deriving a first prediction block (608) at least partly based on an output of a neural net (602) using a first set of parameters; deriving a first encoded prediction error block (614-620) through encoding a difference of the first prediction block and a first input block; encoding (620) the first encoded prediction error block into a bitstream; deriving a first reconstructed prediction error block (624) from the first encoded prediction error block; deriving a training signal (628) from one or both of the first encoded prediction error block and/or the first reconstructed prediction error block (624); retraining (630) the neural net (602) with the training signal (628) to obtain a second set of parameters for the neural net (602); deriving a second prediction block (608) at least partly based on an output of the neural net using the second set of parameters; deriving a second encoded prediction error block (614-620) through encoding a difference of the second prediction block and a second input block; and encoding (620) the second encoded prediction error block into a bitstream. The invention relates to image or video encoding or decoding, especially by online training a neural network (602) that is in the prediction loop.