检索结果-内蒙古大学图书馆

A three-branch deep neural network for diagnosing respiratory sounds

Neural Computing and Applications 2024年第35期36卷 22611-22631页

作者： Imani, Maryam Ghassemian, Hassan Image Processing and Information Analysis Lab Faculty of Electrical and Computer Engineering Tarbiat Modares University Tehran Iran

Finding an accurate model is essential for classification of respiratory pathologies through extraction and fusion of respiratory sounds’ features. To handle the unlabeled data, a sequence of autoencoders are used for data augmentation. A deep neural network framework is proposed to extract three types of features: 1-Features based on the human auditory system, using Mel-frequency cepstral coefficients (MFCCs), 2-Temporal features contained in the sequence of sound signal using the long short-term memory (LSTM) network, and 3-The nonlinear and complex relationship among temporal characteristics in neighborhood regions using a two-dimensional (2D) convolutional neural network (CNN) applied to the sound sequence converted to a 2D time array. Three branches are fused through some fully connected layers. The ICBHI 2017 sound database is used in two cases of 6 and 3 pathological classes. In the case of 6-classes database, 98.72% overall accuracy, 98.46% kappa coefficient, 99.66% sensitivity, 98.70% specificity and 99.70% F1-Sscore is provided. In the case of 3-classes database, 97.18% overall accuracy, 95.77% kappa coefficient, 98.31% sensitivity, 99.16% specificity and 98.93% F1-score are achieved. In contrast to the many researchers that are applying CNN on the Mel spectrogram of the audios, CNN is applied to the 2D form of the time series to find the hidden relationship among the time instants in local regions. Moreover, fusion of these hidden features with the LSTM and MFCC features leads to an accurate multiple classification. This work proposes a new deep learning framework for fusion of three types of sound features, which leads to a significant improvement in multiple respiratory infection diagnosing. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

Unsupervised Hyperspectral Image Classification: Spatial and Spectral Feature Fusion with Masked Autoencoders 20

Unsupervised Hyperspectral Image Classification: Spatial and...

引用

20th CSI International Symposium on Artificial Intelligence and Signal Processing, AISP 2024

作者： Mirsharji, Seyed Ali Ghassemian, Hassan Tarbiat Modares University Image Processing and Information Analysis Lab. Faculty of Electrical and Computer Engineering Tehran Iran

ISBN: (纸本)9798350383942

In this study, we present an innovative unsupervised hyperspectral image classification method using a dual-branch architecture that merges spatial and spectral feature extraction. Our unique approach employs masked autoencoders, significantly outperforming traditional methods with an impressive overall accuracy of 97.1%. The paper details the model's performance evaluation, offers visual insights into its classification capabilities, and compares it with existing techniques, demonstrating its effectiveness and potential for advancing remote sensing applications. © 2024 IEEE.

关键词： Image classification

来源：评论

学校读者我要写书评

暂无评论

Claim Check-Worthiness Detection: How Well do LLMs Grasp Annotation Guidelines? 7

Claim Check-Worthiness Detection: How Well do LLMs Grasp Ann...

引用

7th Fact Extraction and VERification Workshop, FEVER 2024

作者： Majer, Laura Šnajder, Jan Text Analysis and Knowledge Engineering Lab University of Zagreb Faculty of Electrical Engineering and Computing Croatia

ISBN: (纸本)9798891761728

The rising threat of disinformation underscores the need to fully or partially automate the fact-checking process. Identifying text segments requiring fact-checking is known as claim detection (CD) and claim check-worthiness detection (CW), the latter incorporating complex domain-specific criteria of worthiness and often framed as a ranking task. Zero- and few-shot LLM prompting is an attractive option for both tasks, as it bypasses the need for labeled datasets and allows verbalized claim and worthiness criteria to be directly used for prompting. We evaluate the LLMs’ predictive accuracy on five CD/CW datasets from diverse domains, using corresponding annotation guidelines in prompts. We examine two key aspects: (1) how to best distill factuality and worthiness criteria into a prompt, and (2) how much context to provide for each claim. To this end, we experiment with different levels of prompt verbosity and varying amounts of contextual information given to the model. We additionally evaluate the top-performing models with ranking metrics, resembling prioritization done by fact-checkers. Our results show that optimal prompt verbosity varies, meta-data alone adds more performance boost than co-text, and confidence scores can be directly used to produce reliable check-worthiness rankings. © 2024 Association for Computational Linguistics.

关键词： Computational linguistics

来源：评论

学校读者我要写书评

暂无评论

Unsupervised Change Detection in SAR Images Using a Six-Branch CNN and Adaptive Window Approach 31

Unsupervised Change Detection in SAR Images Using a Six-Bran...

引用

31st International Conference on electrical engineering, ICEE 2023

作者： Kakoolvand, Abbas Imani, Maryam Ghassemian, Hassan Tarbiat Modares University Image Processing and Information Analysis Lab Faculty of Electrical and Computer Engineering Tehran Iran

ISBN: (纸本)9798350312560

Change detection is one of the important and hot topics in remote sensing. Adaptive windowing approaches can preserve image details while reduce noise in the process of change detection. In the proposed method, two difference images (DIs) are obtained by using the adaptive window approach. Some fake labels are provided from these DIs. Neural networks have a good performance in image processing. To use this advantage, a six-branch convolutional neural network (CNN) is trained using the fake labels. Using these six branches with utilizing the adaptive windows, the network can preserve image detail while reduce noise. The proposed method based on three criteria (PCC, Kappa, and F1 score) has the best results in two datasets and has results close to the best method in other datasets. © 2023 IEEE.

关键词： Synthetic aperture radar

来源：评论

学校读者我要写书评

暂无评论

Fusion of Multi-Level CNN With LBP Features For Facial Emotion Recognition 31

Fusion of Multi-Level CNN With LBP Features For Facial Emoti...

引用

31st International Conference on electrical engineering, ICEE 2023

作者： Bahmanabady, Ehsan Imani, Maryam Ghassemian, Hassan Tarbiat Modares University Image Processing and Information Analysis Lab Faculty of Electrical and Computer Engineering Tehran Iran

ISBN: (纸本)9798350312560

A facial emotion recognition framework is proposed in this work. The convolutional neural network (CNN) has high ability in extraction of hierarchical spatial features from low level texture characteristics to high level contextual features. A simple CNN model with three layers is suggested in this paper where the features extracted in all layers containing multi-level features are activated and used for classification. In addition, the local binary pattern (LBP) descriptor is used to extract discriminative features from the spatial structure of the input image. Therefore, four feature sources are provided by multi levels of CNN and the LBP descriptor. Each feature source is used for facial emotion recognition by applying to the support vector machine (SVM) classier. Finally, the majority voting rule is used for decision fusion to provide the final emotional label of each given face image. The proposed method with 84% overall accuracy, 83% weighted F1-score and 81% kappa coefficient provides the best performance compared to LBP, multi-level CNN and two-dimensional principal component analysis (2DPCA) methods. © 2023 IEEE.

关键词： Emotion Recognition

来源：评论

学校读者我要写书评

暂无评论

Dynamically-Tunable Narrowband Color Sensor Compatible with CMOS Technology

引用

IEEE Sensors Journal 2025年第11期25卷 19117-19124页

作者： Asl, Akbar Beheshti Ahmadi, Hodjat Rostami, Ali Faculty of Electrical and Computer Engineering Tabriz Iran Industrial Park of Advanced Technologies SP-EPT Lab. ASEPE Company Tabriz Iran

Color sensors have broad applications in spectroscopy, medical imaging, and CMOS-based cameras. One of the fundamental challenges in this field is implementing a dynamically tunable filter capable of covering the visible spectrum;hence, designing a tunable filter with high spectral resolution and a narrow bandwidth frequency response is essential. In this work, a multilayer color sensor based on Fabry-Pérot resonance is designed, offering the capability for static and dynamic tuning of the transmitted wavelength and the ability to detect different colors in an integrated device, including a filter and detector. The filter comprises four parts: blue, green, yellow-orange, and red. The detector is a simple PN photodiode. The dynamic adjustment is performed via the voltage applied to the filter. In addition to the dynamic tunability, a key characteristic of this structure is its bandwidth, which remains consistently below 9, 8.5, 8, and 11.5 nm for blue, green, yellow-orange, and red regions, respectively. Notably, the materials used in this structure have been selected to be compatible with CMOS technology. Another feature of this sensor is its 50 nm spectral shift for each specified spectrum, achieved with a 15-volt bias. Furthermore, this device presents minuscule crosstalk (below 5%) compared to other devices. © 2001-2012 IEEE.

关键词： CMOS integrated circuits

来源：评论

学校读者我要写书评

暂无评论

On Dataset Transferability in Active Learning for Transformers 61

On Dataset Transferability in Active Learning for Transforme...

引用

Findings of the Association for Computational Linguistics, ACL 2023

作者： Jelenić, Fran Jukić, Josip Drobac, Nina Šnajder, Jan University of Zagreb Faculty of Electrical Engineering and Computing Text Analysis and Knowledge Engineering Lab Croatia

ISBN: (纸本)9781959429623

Active learning (AL) aims to reduce labeling costs by querying the examples most beneficial for model learning. While the effectiveness of AL for fine-tuning transformer-based pre-trained language models (PLMs) has been demonstrated, it is less clear to what extent the AL gains obtained with one model transfer to others. We consider the problem of transferability of actively acquired datasets in text classification and investigate whether AL gains persist when a dataset built using AL coupled with a specific PLM is used to train a different PLM. We link the AL dataset transferability to the similarity of instances queried by the different PLMs and show that AL methods with similar acquisition sequences produce highly transferable datasets regardless of the models used. Additionally, we show that the similarity of acquisition sequences is influenced more by the choice of the AL method than the choice of the model. © 2023 Association for Computational Linguistics.

关键词： Classification (of information)

来源：评论

学校读者我要写书评

暂无评论

ALANNO: An Active Learning Annotation System for Mortals 17

ALANNO: An Active Learning Annotation System for Mortals

引用

17th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2023

作者： Jukić, Josip Jelenić, Fran Bićanić, Miroslav Šnajder, Jan University of Zagreb Faculty of Electrical Engineering and Computing Text Analysis and Knowledge Engineering Lab Croatia

ISBN: (纸本)9781959429456

Supervised machine learning has become the cornerstone of today’s data-driven society, increasing the need for labeled data. However, the process of acquiring labels is often expensive and tedious. One possible remedy is to use active learning (AL) – a special family of machine learning algorithms designed to reduce labeling costs. Although AL has been successful in practice, a number of practical challenges hinder its effectiveness and are often overlooked in existing AL annotation tools. To address these challenges, we developed ALANNO, an open-source annotation system for NLP tasks equipped with features to make AL effective in real-world annotation projects. ALANNO facilitates annotation management in a multi-annotator setup and supports a variety of AL methods and underlying models, which are easily configurable and extensible. © 2023 Association for Computational Linguistics.

关键词： Learning algorithms

来源：评论

学校读者我要写书评

暂无评论

Deep Curriculum Learning for PolSAR Image Classification 12

Deep Curriculum Learning for PolSAR Image Classification

引用

12th Iranian/2nd International Conference on Machine Vision and Image Processing, MVIP 2022

作者： Mousavi, Hamidreza Imani, Maryam Ghassemian, Hassan Image Processing and Information Analysis Lab Faculty of Electrical and Computer Engineering Tehran Iran

ISBN: (纸本)9781665412162

Following the great success of curriculum learning in the area of machine learning, a novel deep curriculum learning method proposed in this paper, entitled DCL, particularly for the classification of fully polarimetric synthetic aperture radar (PolSAR) data. This method utilizes the entropy-alpha target decomposition method to estimate the degree of complexity of each PolSAR image patch before applying it to the convolutional neural network (CNN). Also, an accumulative mini-batch pacing function is used to introduce more difficult patches to CNN. Experiments on the widely used data set of AIRSAR Flevoland reveal that the proposed curriculum learning method can not only increase classification accuracy but also lead to faster training convergence. © 2022 IEEE.

关键词： Synthetic aperture radar

来源：评论

学校读者我要写书评

暂无评论

Theoretical analysis and design of a dual-wavelength and selectable all-optical broadband QDs semiconductor optical amplifier (QDs-SOA) with inhomogeneous broadening

引用

Optical and Quantum Electronics 2025年第2期57卷 1-26页

作者： Eyvazi, Mahdiyeh Yadipour, Reza Rostami, Ali Rostami, Parisa Mirtagioglu, Hamid Faculty of Electrical and Computer Engineering University of Tabriz Tabriz*** Iran Faculty of Electrical and Computer Engineering University of Tabriz Tabriz*** Iran SP-EPT Lab ASEPE Company Industrial Park of Advanced Technologies Tabriz Iran Faculty of Medicine Tabriz University of Medical Science Tabriz Iran Department of Statistics Faculty of Science and Literature University of Bitlis Eren Bitlis Turkey

This study delves into the significant role played by Quantum Dot Semiconductor Optical Amplifiers (QD-SOAs) in meeting the ever-growing bandwidth demands. QD-SOAs offer a unique blend of cost-effectiveness, integration capabilities, wide bandwidth, rapid responsiveness, robust power output, stability, and spectral adaptability, driving notable advancements in optical communication systems. In this work, we introduce a novel two-wavelength amplifier structure based on Quantum Dot Semiconductor Optical Amplifiers (QD-SOAs) that utilizes quantum dots of different sizes to achieve efficient amplification at specific mid-infrared wavelengths. This innovative approach, which incorporates quantum dots with varying sizes, enables enhanced performance by optimizing the amplification process for each specific wavelength. Furthermore, this work demonstrates the use of tailored optical pumping mechanisms that enhance the carrier recovery process and reduce carrier relaxation times in the active region. This novel optical pumping technique leads to a significant increase in the efficiency and speed of the amplifier, distinguishing this study from others in the field. Simulation results provide detailed insights into the complex interplay between carrier interactions and gain spectra, offering a comprehensive understanding of QD-SOA operational dynamics. The proposed Quantum Dot Semiconductor Optical Amplifier (QD-SOA) achieves significant advancements in optical communication, offering maximum amplification rates of 26.9 and 19.9 times for QD1 and QD2, respectively, and bandwidths of 12 THz and 15 THz. The study highlights the role of quantum dot size, homogeneous and inhomogeneous broadening, and optical pumping in enhancing gain and performance, demonstrating the potential of QD-SOAs for high-gain, wide-bandwidth applications in photonic systems. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Semiconductor quantum dots

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：