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Perturbation-based methods for explaining deep neural networks: A survey

Pattern recognition letters, 2021-10, Vol.150, p.228-234

2021

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Deep k-Means: Jointly clustering with k-Means and learning representations

Pattern recognition letters, 2020-10, Vol.138, p.185-192

2020

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Trends in IoT based solutions for health care: Moving AI to the edge

Pattern recognition letters, 2020-07, Vol.135, p.346-353

2020

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Machine Learning for Cultural Heritage: A Survey

Pattern recognition letters, 2020-05, Vol.133, p.102-108

2020

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Detecting Parkinson’s disease with sustained phonation and speech signals using machine learning techniques

Pattern recognition letters, 2019-07, Vol.125, p.55-62

2019

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Representation learning for very short texts using weighted word embedding aggregation

Pattern recognition letters, 2016-09, Vol.80, p.150-156

2016

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Large group activity security risk assessment and risk early warning based on random forest algorithm

Pattern recognition letters, 2021-04, Vol.144, p.1-5

2021

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Interactive deep learning method for segmenting moving objects

Pattern recognition letters, 2017-09, Vol.96, p.66-75

2017

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A bagging SVM to learn from positive and unlabeled examples

Pattern recognition letters, 2014-02, Vol.37, p.201-209

2014

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Leveraging recent advances in deep learning for audio-Visual emotion recognition

Pattern recognition letters, 2021-06, Vol.146, p.1-7

2021

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Automated invasive ductal carcinoma detection based using deep transfer learning with whole-slide images

Pattern recognition letters, 2020-05, Vol.133, p.232-239

2020

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PASTLE: Pivot-aided space transformation for local explanations

Pattern recognition letters, 2021-09, Vol.149, p.67-74

2021

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Unsupervised Deep Learning based Variational Autoencoder Model for COVID-19 Diagnosis and Classification

Pattern recognition letters, 2021-11, Vol.151, p.267-274

2021

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Transforming gradient-based techniques into interpretable methods

Pattern recognition letters, 2024-08, Vol.184, p.66-73

2024

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Measuring the class-imbalance extent of multi-class problems

Pattern recognition letters, 2017-10, Vol.98, p.32-38

2017

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Special section: Best papers of the international conference on pattern recognition and artificial intelligence (ICPRAI) 2022

Pattern recognition letters, 2024-01, Vol.177, p.150

2024

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KU-HAR: An open dataset for heterogeneous human activity recognition

Pattern recognition letters, 2021-06, Vol.146, p.46-54

2021

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A simple, robust and fast method for the perspective-n-point Problem

Pattern recognition letters, 2018-06, Vol.108, p.31-37

2018

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Weak supervision for generating pixel–level annotations in scene text segmentation

Pattern recognition letters, 2020-10, Vol.138, p.1-7

2020

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Handwritten isolated Bangla compound character recognition: A new benchmark using a novel deep learning approach

Pattern recognition letters, 2017-04, Vol.90, p.15-21

2017

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CLS-DETR: A DETR-series object detection network using classification information to accelerate convergence

Pattern recognition letters, 2023-01, Vol.165, p.168-175

2023

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A novel unsupervised ensemble framework using concept-based linguistic methods and machine learning for twitter sentiment analysis

Pattern recognition letters, 2022-06, Vol.158, p.80-86

2022

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Pattern recognition and artificial intelligence techniques for cultural heritage

Pattern recognition letters, 2020-10, Vol.138, p.23-29

2020

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Content bias in deep learning image age approximation: A new approach towards better explainability

Pattern recognition letters, 2024-06, Vol.182, p.90-96

2024

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Feature perturbation augmentation for reliable evaluation of importance estimators in neural networks

Pattern recognition letters, 2023-12, Vol.176, p.131-139

2023

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Perturbation-based methods for explaining deep neural networks: A survey

Deep k-Means: Jointly clustering with k-Means and learning representations

Trends in IoT based solutions for health care: Moving AI to the edge

Machine Learning for Cultural Heritage: A Survey

Detecting Parkinson’s disease with sustained phonation and speech signals using machine learning techniques

Representation learning for very short texts using weighted word embedding aggregation

Large group activity security risk assessment and risk early warning based on random forest algorithm

Interactive deep learning method for segmenting moving objects

A bagging SVM to learn from positive and unlabeled examples

Leveraging recent advances in deep learning for audio-Visual emotion recognition

Automated invasive ductal carcinoma detection based using deep transfer learning with whole-slide images

PASTLE: Pivot-aided space transformation for local explanations

Unsupervised Deep Learning based Variational Autoencoder Model for COVID-19 Diagnosis and Classification

Transforming gradient-based techniques into interpretable methods

Measuring the class-imbalance extent of multi-class problems

Special section: Best papers of the international conference on pattern recognition and artificial intelligence (ICPRAI) 2022

KU-HAR: An open dataset for heterogeneous human activity recognition

A simple, robust and fast method for the perspective-n-point Problem

Weak supervision for generating pixel–level annotations in scene text segmentation

Handwritten isolated Bangla compound character recognition: A new benchmark using a novel deep learning approach

CLS-DETR: A DETR-series object detection network using classification information to accelerate convergence

A novel unsupervised ensemble framework using concept-based linguistic methods and machine learning for twitter sentiment analysis

Pattern recognition and artificial intelligence techniques for cultural heritage

Content bias in deep learning image age approximation: A new approach towards better explainability

Feature perturbation augmentation for reliable evaluation of importance estimators in neural networks

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