Open Access. Powered by Scholars. Published by Universities.®

Digital Commons Network™

Open Access. Powered by Scholars. Published by Universities.®

2021

Discipline
Institution
Keyword
Publication
Publication Type
File Type

Articles 189331 - 189360 of 195995

Full-Text Articles in Entire DC Network

A Rationale-Based Lifelong Learning Framework With Pseudo-Sample Replay Enhancement, Kasidis Kanwatchara Jan 2021

A Rationale-Based Lifelong Learning Framework With Pseudo-Sample Replay Enhancement, Kasidis Kanwatchara

Chulalongkorn University Theses and Dissertations (Chula ETD)

Lifelong learning (LL) is a machine learning paradigm in which a learner is sequentially trained on a stream of new tasks while preventing learned knowledge from being forgotten. To achieve lifelong language learning, pseudo-rehearsal methods leverage samples generated from a language model to refresh the knowledge of previously learned tasks. Without proper controls, however, these methods could fail to retain the knowledge of complex tasks with longer texts since most of the generated samples are low in quality. To overcome the problem, we propose three specific contributions. First, we utilize double language models, each of which specializes on a specific …

Go to article

Data Augmentation For Thai Natural Language Processing Using Different Tokenization, Patawee Prakrankamanant Jan 2021

Data Augmentation For Thai Natural Language Processing Using Different Tokenization, Patawee Prakrankamanant

Chulalongkorn University Theses and Dissertations (Chula ETD)

Tokenization is one of the most important data pre-processing steps in the text classification task and also one of the main contributing factors in the model performance. However, getting good tokenizations is non-trivial when the input is noisy, and is especially problematic for languages without an explicit word delimiter such as Thai. Therefore, we proposed an alternative data augmentation method to improve the robustness of poor tokenization by using multiple tokenizations. We evaluated the performance of our algorithms on different Thai text classification datasets. The results suggested our augmentation scheme makes the model more robust to tokenization errors and can …

Go to article

Demand Forecasting In Production Planning For Dairy Products Using Machine Learning And Statistical Methods, Chayuth Vithisoontorn Jan 2021

Demand Forecasting In Production Planning For Dairy Products Using Machine Learning And Statistical Methods, Chayuth Vithisoontorn

Chulalongkorn University Theses and Dissertations (Chula ETD)

Demand forecasting is an essential task in manufacturing of every industry. Efficient forecasting relieves the excessive stock and out-of-stock problem, reducing revenue loss. This research performs a direct multistep forecast approach of demand forecasting on 8 dairy products of 5 different dairy production plants with 5-year data. Widely used traditional statistical method and the state of the art deep learning method for sequence problems are picked. ARIMA and LSTM. The models are compared in many aspects, monthly observations against weekly observations, univariate against multivariate, and statistical against deep learning using model error and business metrics. The result shows that both …

Go to article

Performance Improvement Of Cms Simulation Via Loop Transformation, Teerit Ploensin Jan 2021

Performance Improvement Of Cms Simulation Via Loop Transformation, Teerit Ploensin

Chulalongkorn University Theses and Dissertations (Chula ETD)

High performance processor can tackle bottleneck issues by increasing vector lengths and leveling effectiveness of memory hierarchies to address these issue. Manual optimization of code is a difficult task when having multiple architecturedependent transformation. Our goal is to develop a tool that performs source code transformation based on loop optimization techniques, since a loop plays an important role in improving of performance in scientific simulation software. We implement an source-to-source transformation tool based libTooling, a Clang’s library, based on polyhedral model to simplify a loop transformation of CMSSW building pipeline. The tool also can be used for automatically transformation. The …

Go to article

Sentiment Analysis Of Messages On Twitter Related To Covid-19 Using Deep Learning Approach, Chotika Imvimol Jan 2021

Sentiment Analysis Of Messages On Twitter Related To Covid-19 Using Deep Learning Approach, Chotika Imvimol

Chulalongkorn University Theses and Dissertations (Chula ETD)

The widespread situation of the Coronavirus-19 (COVID-19) pandemic is a tangible and pressing concern. Many changes in terms of lifestyle are necessary to reduce the chance of infection. While citizens have gone through different emotions, they share their thoughts and interactions on social media, especially on Twitter. COVID-19 related messages can imply social emotion. This study performs sentiment analysis on tweets and annotated them into six classes of positive and negative feelings consisting of anger, disgust, fear, sadness, joy, and surprise. We analyzed both textual information and historical data. We collected 120,642 unique tweets datasets between 1 January 2020 and …

Go to article

Conformance Checking And Discovery Of Information Service Request Process, Liam Khaosanoi Jan 2021

Conformance Checking And Discovery Of Information Service Request Process, Liam Khaosanoi

Chulalongkorn University Theses and Dissertations (Chula ETD)

Process mining is a form of business process analysis. The approach could support organizations in retrieving structured process information by using recorded process data to discover, monitor and improve the processes. In this work, the process mining technology is applied for conformance checking and discovering an organization’s Information Service Request process in reality as a case study. Currently, the reference model was drawn as a simple flow using Microsoft Word. The proposed method starts with writing a VBA script to extract traces from the drawing that enables the generation of XES file used for modeling the reference process in Petri …

Go to article

Object Detection In Intelligent Billing System For Conveyor Belt Sushi Restaurant, Rangrak Maitriboriruks Jan 2021

Object Detection In Intelligent Billing System For Conveyor Belt Sushi Restaurant, Rangrak Maitriboriruks

Chulalongkorn University Theses and Dissertations (Chula ETD)

Organization must automate wherever and whenever they can, particularly during today’s global changes in daily lifestyles. Trends regarding the use of technology, especially AI has emerged as a key enabler for disruptive innovation. This thesis thus presents the application programming interface of object detector implemented with YOLOv4 and OpenCV for classifying the prices of sushi plates distinguished by colors. The object detector is part of the smart cross-platform mobile application to facilitate billing process for conveyor belt sushi business. The frontend is developed with Flutter to build single codebase for UIs. To handle the variants of image colors resulting from …

Go to article

Adaptive Image Preprocessing And Augmentation For Disease Screening On Multi-Source Chest X-Ray Datasets, Wasunan Chokchaithanakul Jan 2021

Adaptive Image Preprocessing And Augmentation For Disease Screening On Multi-Source Chest X-Ray Datasets, Wasunan Chokchaithanakul

Chulalongkorn University Theses and Dissertations (Chula ETD)

Research on deep learning models for chest radiology applications has increased attention by the public. However, most works focus on developing models using in-domain data, so the significant drawback, when applied in real-world scenarios, was the mismatched data with the training set. Consequently, some models perform inferior at the deployment stage. This work focused on the effects of dataset mismatch on chest radiography and analyzed the methods the overcome the mismatch issues. The lung balance contrast enhancement technique (lung BCET) automatically identifies the lung region and normalizes the image accordingly to improve the robustness of out-of-domain data developed. Additionally, augmentation …

Go to article

A Design Of Fpga Framework For Quantum Computing Simulation, Yaninee Jungjarassub Jan 2021

A Design Of Fpga Framework For Quantum Computing Simulation, Yaninee Jungjarassub

Chulalongkorn University Theses and Dissertations (Chula ETD)

​We use FPGA to optimize the simulation of quantum computing in two aspects. (a) The if-else state is used in place of tensor product calculation. This allows the tensor product of each quantum operator to be generated in a single clock cycle. (b) The pre-calculated lookup ROM is used for estimating the sine and cosine values. This facilitates the computation of quantum gates that are related to angle. To validate our work, we implement our design in VerilogHDL. The performance is evaluated using an FPGA simulator. The result shows a dramatic improvement in the simulation process comparing to those of …

Go to article

Cascading Model For Forex Market Forecasting Using Fundamental And Technical Indicator Data Based On Bert, Arisara Pornwattanavichai Jan 2021

Cascading Model For Forex Market Forecasting Using Fundamental And Technical Indicator Data Based On Bert, Arisara Pornwattanavichai

Chulalongkorn University Theses and Dissertations (Chula ETD)

The foreign exchange rate market is the world's biggest and most liquid financial market, and it's where all currency pairs' exchange rates are set. Since foreign exchange (Forex) rates play a critical role in financial technology and business, many researchers are now interested in forecasting them. The characteristics of Forex data, that include fluctuation, non-linearity, and random walk phenomena, make it difficult for forecasting. Several related studies integrate fundamental data (FD) and technical indicator data to generate Forex forecasting signals (TI). TI is a price pattern-based signal, whereas FD is an indicator of the country's economic conditions. Nevertheless, when it …

Go to article

Travel Time Prediction With Graph Neural Network: A Case Study In Bangkok Thailand, Sathita Buapang Jan 2021

Travel Time Prediction With Graph Neural Network: A Case Study In Bangkok Thailand, Sathita Buapang

Chulalongkorn University Theses and Dissertations (Chula ETD)

Traffic prediction is an essential and challenging task for traffic management and commercial purposes. Machine learning methods for traffic prediction usually treat traffic conditions as time-series due to obvious temporal patterns. Recently, spatial relationships among roads in a road network have also been used to improve traffic prediction. This study proposes a novel method to predict traffic conditions such as speed using a graph convolutional neural network with a spectral adjacency matrix (GCN-Spectral). Unlike a spatial adjacency matrix representing physical connections between road segments, a spectral matrix represents the correlation between road segments regarding traffic conditions. The GCN-Spectral model is …

Go to article

Pulmonary Lesion Classification Using Convolutional Neural Network For Endobronchial Ultrasonogram, Banphatree Khomkham Jan 2021

Pulmonary Lesion Classification Using Convolutional Neural Network For Endobronchial Ultrasonogram, Banphatree Khomkham

Chulalongkorn University Theses and Dissertations (Chula ETD)

This dissertation aims to develop a method to help classify pulmonary lesions from endobronchial ultrasonography images by proposing new features that are extracted from an EBUS image based on medical knowledge and a pulmonary lesion classification framework. The proposed features, namely the adaptive weighted-sum of the upper triangular gray-level co-occurrence matrix and the adaptive weighted-sum of the lower triangular gray-level co-occurrence matrix are used to determine heterogeneity, which is one of the most important characteristics of malignancy. The proposed features together with other standard features are used as input data for the proposed classification framework that uses the weighted ensemble …

Go to article

Thai Tokenizer Invariant Classification Based On Bi-Lstm And Distilbert Encoders, Noppadol Kongsumran Jan 2021

Thai Tokenizer Invariant Classification Based On Bi-Lstm And Distilbert Encoders, Noppadol Kongsumran

Chulalongkorn University Theses and Dissertations (Chula ETD)

Natural language processing (NLP) is a topic in artificial intelligence to teach computer to understand human language. Researchers can feed text of some particular language in any length and type such as characters, words, and sentences into the algorithm to extract a summarized context in terms of numbers. To accept a word array in Thai language, tokenization process is needed to split a text into words because each sentence is written consecutively without any space between words. In general, different tokenizers can produce different sets of words from a single sentence, resulting in uncontrolled accuracies in NLP and related tasks. …

Go to article

Warehouse Processes Improvement Using Lean Six Sigma And Rfid Technology, Pakkaporn Rungruengkultorn Jan 2021

Warehouse Processes Improvement Using Lean Six Sigma And Rfid Technology, Pakkaporn Rungruengkultorn

Chulalongkorn University Theses and Dissertations (Chula ETD)

The warehouse processes are critical to the success of every organization. Thus, a well-managed warehousing process increases an organization's efficiency. The objective of this thesis is to improve warehouse processes in garment manufacturing using Lean Six Sigma and RFID Technology to reduce waste time and non value-added activities of the current processes. Lean Six Sigma is business process improvement technique that combines the tools and principles of Lean and Six Sigma. The DMAIC methodology was employed in this research, which stands for Define, Measure, Analyze, Improve, and Control. Additionally, Model analysis, Value Stream Mapping (VSM), SIPOC charts, and Cause and …

Go to article

Classification Of Abusive Thai Messages In Social Networks Using Deep Learning, Ruangsung Wanasukapunt Jan 2021

Classification Of Abusive Thai Messages In Social Networks Using Deep Learning, Ruangsung Wanasukapunt

Chulalongkorn University Theses and Dissertations (Chula ETD)

Social media has improved on traditional news sources by allowing increased access to information. However, the anonymity social media provides can lead to abusive and hateful speech without detection or repercussion from individuals with malicious intentions. This research develops a binomial and a multinomial classification model for classifying Thai social media text for five categories of abusive content detection in social media that include Rude, Figurative, Dirty, Offensive and Non-Abusive. The experiments demonstrated that DistilBERT achieved the highest F1 score with 0.8510 for the binomial model and 0.9067 for the multinomial model. BiLSTM performed second best with an F1 score …

Go to article

Designing Answer Sets For Thai Advisory Chatbot With Different Talking Styles For Covid-19 Pandemic, Sakolwan Peetaneelavat Jan 2021

Designing Answer Sets For Thai Advisory Chatbot With Different Talking Styles For Covid-19 Pandemic, Sakolwan Peetaneelavat

Chulalongkorn University Theses and Dissertations (Chula ETD)

This research focuses on designing a set of answers for Thai advisory chatbot using a different conversational approach from conventional chatbot for COVID-19 pandemic in order to improve user’s chatbot experience. The research studies how to modify the underlying interactive chatbot language to suit those extrovert and introvert personalities. To evaluate the correctness of answer set design, the author builds two classification models based on Extroversion Text Classification Model (ETCM). Both models utilize the same Logistic Regression algorithm, but different feature selection techniques. The first model relies solely on Term Frequency-Inverse Document Frequency (TF-IDF) property. In contrast, the second model …

Go to article

Considering Neighbor Projection On Neural Based Recommender Systems, Thitiporn Neammanee Jan 2021

Considering Neighbor Projection On Neural Based Recommender Systems, Thitiporn Neammanee

Chulalongkorn University Theses and Dissertations (Chula ETD)

Now, CF is applied with a neural network to make the model more flexible and more accurate. Different neighbors have a different influence on the target user, and different users usually have different rating patterns. Therefore, the proposed method needs to consider two major issues when applying CF with a neural network: the similarity levels between the neighbors and the target user and the user's rating pattern conversion. Thus, the proposed method consists of three main modules to solve the issues mentioned above: rating conversion, similarity module uses, and prediction module. In the experiment, the proposed method is evaluated and …

Go to article

Thai Variable-Length Question Classification For E-Commerce Platform Using Machine Learning With Topic Modeling Feature, Wasu Chunhasomboon Jan 2021

Thai Variable-Length Question Classification For E-Commerce Platform Using Machine Learning With Topic Modeling Feature, Wasu Chunhasomboon

Chulalongkorn University Theses and Dissertations (Chula ETD)

Nowadays, e-commerce platform continuously grows every year and becomes a part of our daily life. However, the application changes from time to time. Either new users or experienced users could face a problem. Several channels, which are FAQ, email, live chat, and call, are provided by e-commerce platform to cope with the problem. FAQ is usually ignored because it is hard to search for the desired answer. The rest channels are applicable. However, the huge number of users causes a bottleneck especially in the special events which delays the users to receive help because customer service agent can reply to …

Go to article

Domestic Customers' Perceived Value Toward Thai Cultural Products, Krittanan Deedenkeeratisakul Jan 2021

Domestic Customers' Perceived Value Toward Thai Cultural Products, Krittanan Deedenkeeratisakul

Chulalongkorn University Theses and Dissertations (Chula ETD)

As Thai cultural identity is one of the remarkable assets in Thai culture and has gained wider attention, there is a growing trend for the market to capture domestic customers' behavior. This study investigates consumers' value perceptions and their intentions to purchase Thai cultural products by extending the theory of consumption value through four values that influence perceived value of product attitude, which also affect purchase intention and customer satisfaction. Online Survey data from 412 people in Thailand were used to test the hypotheses, and content analysis of 9 in-depth interviewees was used to understand the product's perceptions better. The …

Go to article

Development Of A Curriculum Based On Content And Language Integrated Learning And Competency-Based Education For Enhancing Business English Writing Ability Of Undergraduate Students, Meassnguon Saint Jan 2021

Development Of A Curriculum Based On Content And Language Integrated Learning And Competency-Based Education For Enhancing Business English Writing Ability Of Undergraduate Students, Meassnguon Saint

Chulalongkorn University Theses and Dissertations (Chula ETD)

The purposes of this study were 1) to develop a curriculum based on content and language integrated language learning and competency-based education for enhancing business English writing ability of undergraduate students 2) to investigate the effectiveness of a developed curriculum. The research and development process consists of four phases: 1) studying the research problem and significance, and learning approaches, 2) developing a curriculum based on content and language integrated learning and competency-based education, 3) studying the effectiveness of the developed curriculum, and 4) revising and improving the developed curriculum. This pre-experimental research involved 13 undergraduate students in the business major …

Go to article

Impact Of Early Childhood Caries On Oral Health-Related Quality Of Life Among 5-Year-Old Children In Mandalay, Myanmar, Saw Nay Min Jan 2021

Impact Of Early Childhood Caries On Oral Health-Related Quality Of Life Among 5-Year-Old Children In Mandalay, Myanmar, Saw Nay Min

Chulalongkorn University Theses and Dissertations (Chula ETD)

Purpose: The study aimed to develop the cross-cultural adaptation and psychometric properties of the Myanmar Version of SOHO-5 and assess the impact of ECC on oral health quality of life among 5-year-old children in Mandalay using the Myanmar version of the SOHO-5 questionnaire. Materials and methods: The Myanmar SOHO-5 version was conducted with the forward-backward translation method and investigated the content validity, internal consistency, test-retest reliability, construct validity, and discriminant validity on 5-year-old children and their parents in phase I. A cross-sectional study was conducted using a self-administered questionnaire to investigate the impact of ECC and relative factors on the …

Go to article

Approaches For Developing Academic Management Of Secondary Schools In Cambodia Based On The Concept Of Exemplary Leadership, Soksamnang Pheach Jan 2021

Approaches For Developing Academic Management Of Secondary Schools In Cambodia Based On The Concept Of Exemplary Leadership, Soksamnang Pheach

Chulalongkorn University Theses and Dissertations (Chula ETD)

The purposes of this study were 1. to examine the exemplary leadership level of Cambodian secondary school students in Battambang Province and to study the priority needs of academic management development of secondary schools in Cambodia based on the concept of exemplary leadership, 2. to develop the approaches for developing the academic management of secondary schools in Cambodia based on the concept of exemplary leadership. The data were collected from 12 sample schools, choosing one school to represent one district. The study informants included school principals, vice-principal, teachers, and students in Battambang province accounting for 169. The research instrument used …

Go to article

Single Image Super-Resolution Using Capsule Generative Adversarial Network, Amir Hajian Jan 2021

Single Image Super-Resolution Using Capsule Generative Adversarial Network, Amir Hajian

Chulalongkorn University Theses and Dissertations (Chula ETD)

The current research aims to investigate and propose a Generative Adversarial Network (GAN) architecture [53] using capsule network architecture [76] in the discriminator module of the proposed model (Caps-GAN) for Single Image Super-Resolution. Besides, the study aims to develop the proposed SR framework in three scale factors. Finally, the performance of Caps-GAN is compared with other state-of-the-art models. Our Caps-GAN model consists of three fundamental components: the generator module, capsule discriminator module, and combinations of loss functions based on the GAN concept. The proposed generator utilizes the residual in residual dense blocks (RRDB) architecture [28] under a progressively up-sampling framework …

Go to article

Multi-Modal Biometric-Based Human Identification Using Deep Convolutional Siamese Neural Network, Hsu Mon Lei Aung Jan 2021

Multi-Modal Biometric-Based Human Identification Using Deep Convolutional Siamese Neural Network, Hsu Mon Lei Aung

Chulalongkorn University Theses and Dissertations (Chula ETD)

Biometric recognition is a critical task in security control systems. Although face biometric has long been granted the most accepted and practical biometric for human recognition, it can be easily stolen and imitated. It also has challenges getting reliable facial information from the low-resolution camera. In contrast, a gait physical biometric has been recently used for recognition. It can be more complicated to replicate and can also be taken from reliable information from the poor-quality camera. However, human body recognition has remained a problem since the lack of full-body detail within a short distance. Moreover, the unimodal biometric system still …

Go to article

Deep Learning With Attention Mechanism For Iterative Face Super-Resolution, Krit Duangprom Jan 2021

Deep Learning With Attention Mechanism For Iterative Face Super-Resolution, Krit Duangprom

Chulalongkorn University Theses and Dissertations (Chula ETD)

Face images are widely used in many applications, such as face recognition and face identification. Regarding security, face identification is used to track the crimes. However, the camera's low resolution and environmental degradation problem hinders the face application's performance. In this thesis, we study face image super-resolution to restore the image from low-resolution to high-resolution. We proposed deep learning with an attention mechanism for iterative face super-resolution that included an image super-resolution network and face alignment network combined. The input low-resolution image is enlarged into a super-resolution face image. Then, the image has repeatedly estimated the alignment to enhance the …

Go to article

Hybrid Gns3 And Mininet-Wifi Emulator For Survivable Sdn Backbone Network Supporting Wireless Iot Traffic, May Pyone Han Jan 2021

Hybrid Gns3 And Mininet-Wifi Emulator For Survivable Sdn Backbone Network Supporting Wireless Iot Traffic, May Pyone Han

Chulalongkorn University Theses and Dissertations (Chula ETD)

This thesis has designed and implemented an emulated testbed for fault-tolerant delay awareness routing for wireless sensor traffic by using software-defined networking (SDN) at the backbone network. In this work, the hybrid form of GNS3 and Mininet-WiFi emulation network testbed is proposed to build an emulated SDN-based backbone network in GNS3 and an emulated IPv6 over Low Power Personal Area Network (6LoWPAN) in Mininet-WiFi. Three virtual machines are used to set up the hybrid emulated SDN-based network testbed. The Mininet-WiFi platform which is used to build the emulated 6LoWPAN sensor network is installed in two virtual machines separately and the …

Go to article

Deployment Of Rfid, Gps And Iot Technology For Medical Specimen Logistic System, Mya Myet Thwe Chit Jan 2021

Deployment Of Rfid, Gps And Iot Technology For Medical Specimen Logistic System, Mya Myet Thwe Chit

Chulalongkorn University Theses and Dissertations (Chula ETD)

This paper aims to implement a specimen logistic system using RFID technology combined with modern IoT technology in Chulalongkorn hospital. The specimen is a sample collected from the human body. Samples can be urine, saliva, sputum, feces, semen, and other bodily fluids and tissues. Samples are usually collected from the patient and stored in a test tube. Then test tubes are delivered to the corresponding laboratory for examination. Normally, barcodes are tagged over the test tubes for the purpose of recording patient information. In this work, RFID is deployed on the test tube instead for patient data logging. This solution …

Go to article

Simplified Tone Reservation-Based Techniques For Peak-To-Average Power Ratio Reduction Of Orthogonal Frequency Division Multiplexing Signals, Rafee Al Ahsan Jan 2021

Simplified Tone Reservation-Based Techniques For Peak-To-Average Power Ratio Reduction Of Orthogonal Frequency Division Multiplexing Signals, Rafee Al Ahsan

Chulalongkorn University Theses and Dissertations (Chula ETD)

Orthogonal Frequency Division Multiplexing (OFDM) is one of the preferred modulation techniques for modern wireless communications networks, due to its high spectral efficiency and immunity to frequency selective channels. However, OFDM signals are known to suffer from a large peak-to-average power ratio (PAPR). OFDM signals with high PAPR values will inevitably be clipped by the power amplifiers (PA), causing signal distortion and out-of-band radiation, that would lead to the deterioration of bit error rate performance. This thesis focuses on a class of PAPR reduction techniques called tone reservation (TR) techniques, which possesses three desirable features, namely high PAPR reduction gain, …

Go to article

Identification And Counting White Blood Cell Subtypes With Convolutional Neural Network, Singgih Bekti Worsito Jan 2021

Identification And Counting White Blood Cell Subtypes With Convolutional Neural Network, Singgih Bekti Worsito

Chulalongkorn University Theses and Dissertations (Chula ETD)

White blood cell (WBC) has five subtypes namely neutrophil, eosinophil, basophil, lymphocyte, and monocyte which play specific roles in the immune system and against diseases. The object detection model applied to microscopic objects is introduced to assist experts in performing tasks in blood analysis. Unbalanced cell composition of WBC subtypes to be detected is a challenge in building a model in Convolutional Neural Network (CNN). This research aims to build models in recognizing and counting WBC subtypes with neural networks constructed from augmented data enrichment. CNN is demonstrated in this study with the YOLOv5s, YOLOv5l, and YOLOv5x models to detect …

Go to article

Topology Optimization For Cnn Using Neuroevolution, Kevin Richard G. Operiano Jan 2021

Topology Optimization For Cnn Using Neuroevolution, Kevin Richard G. Operiano

Chulalongkorn University Theses and Dissertations (Chula ETD)

In the recent years, the architecture of the convolutional neural networks has become much deeper and more complex to improve their performance. Consequently, they require large datasets and a considerable amount of computational resources. However, in some applications such as medical imaging analysis, datasets are scarce and difficult to collect. In these cases, deep networks cannot be trained enough, which makes them susceptible to overfitting. Moreover, not all institutions have access to abundant computational resources. Designing a small network that performs as well as a deep network requires expertise and a great effort. Neuroevolution is therefore proposed to automatically discover …

Go to article

First Prev Next Last