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Keyword: Convolutional neural networksAI-Based Photography Assessment System using Convolutional Neural Networks
Providing timely and meaningful feedback in photography education is challenging, particularly in large classes where manual assessment can delay skill development. This paper presents M-Stock, an AI-based automated photo evaluation system that uses Convolutional Neural Networks (CNNs) to assess student photography assignments on web browser. M-Stock evaluates both technical aspects (such as lighting, composition, and…
Read MorePerformance Evaluation of Convolutional Neural Networks (CNNs) And VGG on Real Time Face Recognition System
Face Recognition (FR) is considered as a heavily studied topic in computer vision field. The capability to automatically identify and authenticate human’s faces using real-time images is an important aspect in surveillance, security, and other related domains. There are separate applications that help in identifying individuals at specific locations which help in detecting intruders. The…
Read MoreDetection and Counting of Fruit Trees from RGB UAV Images by Convolutional Neural Networks Approach
The use of Unmanned Aerial Vehicle (UAV) can contribute to find solutions and add value to several agricultural problems, favoring thus productivity, better quality control processes and flexible farm management. In addition, the strategies that allow the acquisition and analysis of data from agricultural environments can help optimize current practices such as crop counting. The…
Read MoreTowards Directing Convolutional Neural Networks Using Computational Geometry Algorithms: Application to Handwritten Arabic Character Recognition
Suppose we want to classify a query item Q with a classification model that consists of a large set of predefined classes L and suppose we have a knowledge that indicates to us that the target class of Q belongs to a small subset from L. Naturally, this filtering will improve the accuracy of any…
Read MoreTowards Classification of Shrimp Diseases Using Transferred Convolutional Neural Networks
Vietnam is one of the top 5 largest shrimp exporters globally, and Mekong delta of Vietnam contributes more than 80% of total national production. Along with intensive farming and growing shrimp farming area, diseases are a severe threat to productivity and sustainable development. Timely response to emerging shrimp diseases is critical. Early detection and treatment…
Read MoreObject Classifications by Image Super-Resolution Preprocessing for Convolutional Neural Networks
Blurred small objects produced by cropping, warping, or intrinsically so, are challenging to detect and classify. Therefore, much recent research is focused on feature extraction built on Faster R-CNN and follow-up systems. In particular, RPN, SPP, FPN, SSD, and DSSD are the layered feature extraction methods for multiple object detections and small objects. However, super-resolution…
Read MoreSoftware and Hardware Enhancement of Convolutional Neural Networks on GPGPUs
Convolutional Neural Networks (CNNs) have gained attention in recent years for their ability to perform complex machine learning tasks with high accuracy and resilient to noise of inputs. The time-consuming convolution operations of CNNs pose great challenges to both software as well as hardware designers. To achieve superior performance, a design involves careful concerns between…
Read MoreDouble-Enhanced Convolutional Neural Network for Multi-Stage Classification of Alzheimer’s Disease
Being known as an irreversible neurodegenerative disease which has no cure to date, detection and classification of Alzheimer’s disease (AD) in its early stages is significant so that the deterioration process can be slowed down. Generally, AD can be classified into three major stages, ranging from the “normal control” stage with no symptoms shown, the…
Read MoreHybrid Neural Network Method for Predicting the SOH and RUL of Lithium-Ion Batteries
The use of a battery to power an electrical or electronic system is accompanied by battery management, i.e. a set of measures intended to preserve it for preventative maintenance, thus the cost reduction. This management is generally based on two key parameters, the (remaining useful life) RUL and the (State-of-health) SOH, which relate respectively to…
Read MoreConvolutional Neural Network Based Classification of Patients with Pneumonia using X-ray Lung Images
Analysis and classification of lung diseases using X-ray images is a primary step in the procedure of pneumonia diagnosis, especially in a critical period as pandemic of COVID-19 that is type of pneumonia. Therefore, an automatic method with high accuracy of classification is needed to perform classification of lung diseases due to the increasing number…
Read MoreA Survey on 3D Hand Skeleton and Pose Estimation by Convolutional Neural Network
Restoring, estimating the fully 3D hand skeleton and pose from the image data of the captured sensors/cameras applied in many applications of computer vision and robotics: human-computer interaction; gesture recognition, interactive games, Computer-Aided Design (CAD), sign languages, action recognition, etc. These are applications that flourish in Virtual Reality and Augmented Reality (VR/AR) technologies. Previous survey…
Read MoreDesign of Efficient Convolutional Neural Module Based on An Improved Module
In order to further improve the feature extraction performance of the convolutional neural networks, we focus on the selection and reorganization of key features and suspect that simple changes in the pooling layers can cause changes in the performance of neural networks. According to the conjecture, we design a funnel convolution module, which can filter…
Read MoreComputationally Efficient Explainable AI Framework for Skin Cancer Detection
Skin cancer stands among some of the fastest growing and fatal malignancies of the world as a result early and accurate diagnosis of skin cancer is essential in order to enhance patient survival and treatment prognosis. Conventional methods of diagnosis including dermoscopy and histopathological examinations are expensive and time consuming also subject to inter-observer error.…
Read More3D Facial Feature Tracking with Multimodal Depth Fusion
As models based in artificial intelligence increase in sophistication, there is a higher demand for the integration of hardware components to heighten real-world implementations. Both facial feature tracking and shape-from-focus are known techniques in computer vision. However, the combination of these two elements, particularly in a cost-effective configuration, has not been extensively explored. In this…
Read MoreTransfer and Ensemble Learning in Real-time Accurate Age and Age-group Estimation
Aging is considered to be a complex process in almost every species’ life, which can be studied at a variety of levels of abstraction as well as in different organs. Not surprisingly, biometric characteristics from facial images play a significant role in predicting human’s age. Specifically, automatic age estimation in real-time situation has begun to…
Read MoreA-MnasNet and Image Classification on NXP Bluebox 2.0
Computer Vision is a domain which deals with the challenge of enabling technology with vision capabilities. This goal is accomplished with the use of Convolutional Neural Networks. They are the backbone of implementing vision applications on embedded systems. They are complex but highly efficient in extracting features, thus, enabling embedded systems to perform computer vision…
Read MoreClassifying Garments from Fashion-MNIST Dataset Through CNNs
Online fashion market is constantly growing, and an algorithm capable of identifying garments can help companies in the clothing sales sector to understand the profile of potential buyers and focus on sales targeting specific niches, as well as developing campaigns based on the taste of customers and improve user experience. Artificial Intelligence approaches able to…
Read MoreStandardized UCI-EGO Dataset for Evaluating 3D Hand Pose Estimation on the Point Cloud
To evaluate and compare methods in computer vision, scientists must use a benchmark dataset and unified sets of measurements. The UCI-EGO dataset is a standard benchmark dataset for evaluating Hand Pose Estimation (HPE) on depth images. To build robotic arms that perform complex operations such as human hands, the poses of the human hand need…
Read MoreA Toolkit for the Automatic Analysis of Human Behavior in HCI Applications in the Wild
Nowadays, smartphones and laptops equipped with cameras have become an integral part of our daily lives. The pervasive use of cameras enables the collection of an enormous amount of data, which can be easily extracted through video images processing. This opens up the possibility of using technologies that until now had been restricted to laboratories,…
Read MoreInteractive Virtual Rehabilitation for Aphasic Arabic-Speaking Patients
Objective: Individuals with aphasia often experience significant problems in their daily lives and social participation. Technologies that address speech and language disorders deficit in merging between therapist’s major role and reinforcing the training between sessions at home. It also lacks the Arabic language attention; however, current systems are typically expensive and lack amusement. Moreover, cumulative…
Read MoreClassification of Handwritten Names of Cities and Handwritten Text Recognition using Various Deep Learning Models
This article discusses the problem of handwriting recognition in Kazakh and Russian languages. This area is poorly studied since in the literature there are almost no works in this direction. We have tried to describe various approaches and achievements of recent years in the development of handwritten recognition models in relation to Cyrillic graphics. The…
Read MoreCNN-LSTM Based Model for ECG Arrhythmias and Myocardial Infarction Classification
ECG analysis is commonly used by medical practitioners and cardiologists for monitoring cardiac health. A high-performance automatic ECG classification system is a challenging area because there is difficulty in detecting and clustering various waveforms in the signal, especially in the manual analysis of electrocardiogram (ECG) signals. In this paper, an accurate (ECG) classification and monitoring…
Read MoreA CNN-based Differential Image Processing Approach for Rainfall Classification
With the aim of preventing hydro-geological risks and overcoming the problems of current rain gauges, this paper proposes a low-complexity and cost-effective video rain gauge. In particular, in this paper the authors propose a new approach to rainfall classification based on image processing and video matching process employing convolutional neural networks (CNN). The system consists…
Read MoreDeep Learning Model for A Driver Assistance System to Increase Visibility on A Foggy Road
For many years, a lot of researches have been made to develop Advanced Driver Assistance Systems (ADAS) that are based on integrated systems. The main objective is to help drivers. Hence, keeping them safe under different driving conditions. Visibility for drivers remains the biggest problem faced on the road in an atmosphere of fog. In…
Read MoreTransfer Learning and Fine Tuning in Breast Mammogram Abnormalities Classification on CBIS-DDSM Database
Breast cancer has an important incidence in women mortality worldwide. Currently, mam- mography is considered the gold standard for breast abnormalities screening examinations, since it aids in the early detection and diagnosis of the illness. However, both identification of mass lesions and its malignancy classification is a challenging problem for artificial intelligence. In this work,…
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